This document provides a summary of statistical books in English that are available from a Polish publisher. It lists several books related to statistics, including titles on careers in statistics, probability, Bayesian methods, and multivariate analysis. The summary highlights that internationally recognized statistical societies have declared 2013 the International Year of Statistics to honor achievements in the field. The publisher is promoting important statistics books to join the celebration.
The document is a catalog listing books on mathematical statistics in English. It announces that 2013 was declared the International Year of Statistics by the American Statistical Association. The catalog promotes important books in the field and provides links to view more details on statistical publications.
Statistics is important in chemistry for collecting, analyzing, and presenting quantitative data. It is used in analytical chemistry to detect, identify, and measure unknown chemical compositions using instrumentation techniques. Statistical methods like descriptive statistics are used to summarize sample data using measures like the mean and standard deviation, while inferential statistics draw conclusions from data subject to random variation. Statistics plays a vital role in chemistry research by guiding data collection, interpretation, and presentation to properly characterize and summarize results. It is especially useful for drawing reliable conclusions in chemistry research.
STATISTICAL TOOLS USED IN ANALYTICAL CHEMISTRYkeerthana151
This document provides an overview of statistical concepts related to analytical chemistry. It defines key terms like error, bias, accuracy, and precision. It discusses measures of central tendency, statistical process control charts, and various statistical tests. It provides examples of calculating Kjeldahl nitrogen and describes different types of control charts and statistical tests like t-tests, F-tests, linear regression, and analysis of variance. It lists several references for further information on statistics topics.
1. The document discusses basic research methodology including definitions of research, categories of research such as empirical, theoretical, basic, and applied research.
2. It also covers scientific research steps, quantitative and qualitative data collection, and research design which involves formulating problems, setting objectives, designing studies, and interpreting results.
3. Key aspects of research methodology discussed include hypotheses formulation and testing, various study designs like experimental and observational, and determining appropriate sample sizes.
- Data analysis and interpretation examines data using statistical techniques to answer research questions. It involves examining variables in terms of quantity, quality, attributes, patterns, and relationships.
- There are different types of statistical tests for examining single variables, relationships between two variables, and relationships between multiple independent and dependent variables.
- Analysis of variance (ANOVA) tests for differences across multiple dependent variables based on an independent nominal variable. It uses sums of squares and cross-product matrices.
This document provides an introduction to basic statistics concepts. It instructs students to collect data on the ages of classmates, organize it into a frequency table or graph, and answer questions about the distribution of ages. The document explains that statistics involves gathering, arranging, and presenting numeric data systematically, such as through tables, graphs or by sorting data in ascending or descending order. It defines statistics as the study of collecting, analyzing and interpreting data to address research questions.
Forecasting Academic Performance using Multiple Linear Regressionijtsrd
This document discusses using multiple linear regression to forecast academic performance based on intelligence quotient (IQ) and study hours. The authors collected test score, IQ, and study hour data for 10 students and used the Statistical Package for Social Sciences (SPSS) to analyze the data. They found that IQ and study hours significantly predicted test scores, with IQ and study hours explaining 91% of the variance in test scores. For every one unit increase in IQ, test scores increased by 0.509 units on average, and for every one unit increase in study hours, test scores increased by 0.467 units on average. The authors conclude that regression is a useful statistical method for educational research and that this analysis can help students and teachers improve academic performance
The document is a catalog listing books on mathematical statistics in English. It announces that 2013 was declared the International Year of Statistics by the American Statistical Association. The catalog promotes important books in the field and provides links to view more details on statistical publications.
Statistics is important in chemistry for collecting, analyzing, and presenting quantitative data. It is used in analytical chemistry to detect, identify, and measure unknown chemical compositions using instrumentation techniques. Statistical methods like descriptive statistics are used to summarize sample data using measures like the mean and standard deviation, while inferential statistics draw conclusions from data subject to random variation. Statistics plays a vital role in chemistry research by guiding data collection, interpretation, and presentation to properly characterize and summarize results. It is especially useful for drawing reliable conclusions in chemistry research.
STATISTICAL TOOLS USED IN ANALYTICAL CHEMISTRYkeerthana151
This document provides an overview of statistical concepts related to analytical chemistry. It defines key terms like error, bias, accuracy, and precision. It discusses measures of central tendency, statistical process control charts, and various statistical tests. It provides examples of calculating Kjeldahl nitrogen and describes different types of control charts and statistical tests like t-tests, F-tests, linear regression, and analysis of variance. It lists several references for further information on statistics topics.
1. The document discusses basic research methodology including definitions of research, categories of research such as empirical, theoretical, basic, and applied research.
2. It also covers scientific research steps, quantitative and qualitative data collection, and research design which involves formulating problems, setting objectives, designing studies, and interpreting results.
3. Key aspects of research methodology discussed include hypotheses formulation and testing, various study designs like experimental and observational, and determining appropriate sample sizes.
- Data analysis and interpretation examines data using statistical techniques to answer research questions. It involves examining variables in terms of quantity, quality, attributes, patterns, and relationships.
- There are different types of statistical tests for examining single variables, relationships between two variables, and relationships between multiple independent and dependent variables.
- Analysis of variance (ANOVA) tests for differences across multiple dependent variables based on an independent nominal variable. It uses sums of squares and cross-product matrices.
This document provides an introduction to basic statistics concepts. It instructs students to collect data on the ages of classmates, organize it into a frequency table or graph, and answer questions about the distribution of ages. The document explains that statistics involves gathering, arranging, and presenting numeric data systematically, such as through tables, graphs or by sorting data in ascending or descending order. It defines statistics as the study of collecting, analyzing and interpreting data to address research questions.
Forecasting Academic Performance using Multiple Linear Regressionijtsrd
This document discusses using multiple linear regression to forecast academic performance based on intelligence quotient (IQ) and study hours. The authors collected test score, IQ, and study hour data for 10 students and used the Statistical Package for Social Sciences (SPSS) to analyze the data. They found that IQ and study hours significantly predicted test scores, with IQ and study hours explaining 91% of the variance in test scores. For every one unit increase in IQ, test scores increased by 0.509 units on average, and for every one unit increase in study hours, test scores increased by 0.467 units on average. The authors conclude that regression is a useful statistical method for educational research and that this analysis can help students and teachers improve academic performance
[David j. sheskin]_handbook_of_parametric_and_nonpNERRU
This document provides a preface and overview of the third edition of the Handbook of Parametric and Nonparametric Statistical Procedures. The handbook aims to serve as a comprehensive reference for statistical procedures, with an emphasis on practical applications over theory. It covers a wide range of univariate and bivariate statistical tests and measures of association across over 30 chapters. New material has been added to various chapters, expanding the coverage of topics like experimental design, probability, missing data techniques, and specific statistical tests.
This document discusses the different meanings and definitions of statistics. It explains that statistics has three different meanings: (1) plural sense referring to numerical facts and figures collected systematically, (2) singular sense referring to the science of collecting, analyzing, and presenting numerical data, and (3) plural of the word "statistic" referring to numerical quantities calculated from samples. The document also provides several definitions of statistics from different authors, describing it as the science of collecting, organizing, and interpreting quantitative data.
This document provides an overview of quantitative data analysis and statistical tests. It discusses research questions, variables, descriptive and inferential statistics. Common statistical tests are explained like the Mann-Whitney U test, Spearman rank correlation, Kruskal-Wallis test, t-test, Pearson correlation, ANOVA, and chi-square test. Factors to consider when selecting a statistical test are highlighted like level of data, number of groups, independent or related groups, and data distribution. The document emphasizes keeping analyses simple and statistics in context of discussion.
Statistics can be defined in both a singular and plural sense. In the singular sense, it refers to statistical methods for collecting, analyzing, and interpreting numerical data. In the plural sense, it refers to the actual numerical facts or data collected. Statistics involves systematically collecting, organizing, presenting, analyzing, and interpreting numerical data to describe features and characteristics. It allows for comparing facts, establishing relationships, and facilitating policymaking and decision making. However, statistics only studies aggregates and averages, not individual cases, and results are true only on average. It also requires properly contextualizing and referencing results.
This document provides an overview of statistical analysis for nursing research. It defines key terms like statistics, data analysis, and population. It outlines the specific objectives of understanding statistical analysis and applying it to nursing research skillfully. It also describes the various types of statistical analysis including descriptive statistics, inferential statistics, parametric and nonparametric tests. Finally, it discusses the steps in statistical analysis, available computer programs, uses of statistical analysis in different fields including nursing, and advantages and disadvantages of statistical analysis.
This document discusses statistical analysis using SPSS. It describes descriptive statistics, which present data in a usable form by describing frequency, central tendency, and dispersion. Inferential statistics make broader generalizations from samples to populations using hypothesis testing. Hypothesis testing involves research hypotheses, null hypotheses, levels of significance, and type I and II errors. Choosing an appropriate statistical test depends on the hypothesis and measurement levels of the variables. SPSS is a comprehensive system for statistical analysis that can analyze many file types and generate reports and statistics.
SPSS is a popular statistical software package that allows users to perform complex data analysis with simple instructions. It requires variables, data, measurement scales, and a code book to be defined. The document then describes different variable types (independent, dependent), measurement scales (nominal, ordinal, interval, ratio), how to start and use SPSS, and basic functions for data entry, analysis including frequencies, descriptives, correlation, and reliability which can be measured using Cronbach's alpha.
This document provides information and guidelines for students completing an econometrics project for ECON 762. It discusses acceptable topics, data sources, the required proposal and progress report, as well as formatting and content expectations for the final paper. Students must submit a 1-2 page proposal by February 13 describing their research question, data, and methods. A progress report is due April 7 to describe preliminary work and any issues encountered. The final paper should be 15-30 pages following a standard format with sections on introduction, literature review, data and methods, results, and conclusion.
This document discusses the role and importance of statistics in scientific research. It begins by defining statistics as the science of learning from data and communicating uncertainty. Statistics are important for summarizing, analyzing, and drawing inferences from data in research studies. They also allow researchers to effectively present their findings and support their conclusions. The document then describes how statistics are used and are important in many fields of scientific research like biology, economics, physics, and more. It also provides examples of statistical terms commonly used in research studies and some common misuses of statistics.
Planning the analysis and interpretation of resseaech dataramil12345
The document outlines the researcher's plan for analyzing qualitative and quantitative data collected in a study. It discusses analyzing both types of data, including describing data, identifying typical and atypical findings, and answering research questions. Methods for analyzing qualitative data include historical analysis, inductive analysis, deductive analysis, and content analysis. Quantitative data analysis relies on statistical techniques to summarize data, identify similarities and differences between groups, and test hypotheses. Common statistical analyses include descriptive analysis, univariate analysis, bivariate analysis, multivariate analysis, and comparative analysis. The document also provides guidance on choosing appropriate statistical tests based on research questions, data type, and hypotheses.
Commonly Used Statistics in Survey ResearchPat Barlow
This is a version of our "commonly used statistics" presentation that has been modified to address the commonly used statistics in survey research and analysis. It is intended to give an *overview* of the various uses of these tests as they apply to survey research questions rather than the point-and-click calculations involved in running the statistics.
This document provides an overview of quantitative analysis techniques using SPSS, including data manipulation, transformation, and cleaning methods. It also covers univariate, bivariate, and other statistical analysis methods for exploring relationships between variables and differences between groups. Specific techniques discussed include computing new variables, recoding, selecting cases, imputing missing values, aggregating data, sorting, merging files, descriptive statistics, correlations, regressions, t-tests, ANOVA, non-parametric tests, and more.
This document discusses various quantitative data analysis techniques for research. It covers describing and summarizing data, identifying relationships between variables, comparing variables, and forecasting outcomes. The five most important methods are identified as mean, standard deviation, regression, sample size determination, and hypothesis testing. Parametric and non-parametric techniques are also discussed. Four levels of data measurement are defined: nominal, ordinal, interval, and ratio data. Examples are provided for coding nominal/ordinal data and visualizing data through graphs and charts. Statistical tests like the t-test, ANOVA, and chi-square are also summarized.
This document provides an overview of data analysis and statistics concepts for a training session. It begins with an agenda outlining topics like descriptive statistics, inferential statistics, and independent vs dependent samples. Descriptive statistics concepts covered include measures of central tendency (mean, median, mode), measures of variability (range, standard deviation), and charts. Inferential statistics discusses estimating population parameters, hypothesis testing, and statistical tests like t-tests, ANOVA, and chi-squared. The document provides examples and online simulation tools. It concludes with some practical tips for data analysis like checking for errors, reviewing findings early, and consulting a statistician on analysis plans.
The document discusses various statistical tools used in research including measures of central tendency (mean, median, mode), measures of dispersion (standard deviation, interquartile range, coefficient of variation), t-tests, ANOVA, regression, correlation and more. It provides examples of when each tool would be used, such as using regression to model relationships between variables or ANOVA to test for differences between group means. The document aims to increase awareness of these common statistical tools for analyzing data in research studies across various fields.
Introduction to statistics for social sciences 1Minal Jadeja
This document provides an introduction to statistics. It defines statistics as the collection, presentation, analysis, and interpretation of numerical data. Statistics can refer to either quantitative information or a method of dealing with quantitative or qualitative information. There are two main approaches in statistics - descriptive statistics, which deals with presenting data in tables or graphs to get a general picture of a sample, and inferential statistics, which involves techniques for making inferences about a whole population based on a sample. Some key uses and applications of statistics include showing how samples differ from normal distributions, facilitating comparisons, simplifying messages in data, helping to formulate and test hypotheses, and aiding in prediction and inference. However, there are also some limitations to consider with statistics, such
Data collection and interpretation SBL1023SHAKINAZ DESA
This document provides information on data collection, analysis, interpretation, and presentation for experimental reports. It discusses analyzing data using relevant software, interpreting experimental results, discussing limitations, and using graphical and written formats to present findings. Key points include using analysis to describe, summarize, identify relationships and differences between variables, and forecast outcomes, as well as interpreting results by determining what was learned, expected, and surprising in order to draw conclusions.
This document provides an overview of key concepts for analyzing medical data from a research perspective, including:
- Statistical concepts important for medical licensing exams like scales of measurement, distributions, hypothesis testing, and study designs.
- How to determine what data is available to answer a clinical question, locate existing datasets, and analyze/interpret findings using software like Excel and SPSS.
- Resources for further learning about epidemiology, health statistics, diagnostic tests, and using statistical software.
This document discusses exploratory data analysis techniques including boxplots and five-number summaries. It explains how to organize and graph data using histograms, frequency polygons, stem-and-leaf plots, and box-and-whisker plots. The five important values used in a boxplot are the minimum, first quartile, median, third quartile, and maximum. An example constructs a boxplot for a stockbroker's daily client numbers over 11 days.
This document provides an overview of quantitative data analysis techniques used in sociology. It defines key terms like univariate analysis, bivariate analysis, and multivariate analysis. Univariate analysis examines one variable at a time through measures like frequency distributions, averages, and standard deviation. Bivariate analysis examines the relationship between two variables using cross-tabulation tables. Multivariate analysis examines relationships between multiple variables simultaneously. The document also discusses data coding, codebook construction, and ethical considerations in quantitative data analysis.
Este documento describe los conceptos clave de la organización. Explica que la organización es importante para lograr la eficiencia a través de la coordinación de recursos. También describe los diferentes tipos de recursos (humanos, materiales, técnicos) y estructuras organizacionales (lineal, funcional, lineal-funcional, staff). Además, explica conceptos como departamentalización y liderazgo que son fundamentales para la organización.
La seguridad de la información es fundamental para las administraciones públicas. El documento describe los servicios que ofrece INTECO para mejorar la seguridad, incluyendo el Centro de Respuesta a Incidentes de Seguridad (INTECO-CERT) que ayuda a pymes y ciudadanos con servicios gratuitos como detección de amenazas, formación y soporte técnico. También se mencionan las acciones de la Agrupación Empresarial Innovadora en Seguridad (AEI Seguridad) para fomentar la innovación y formación en nuevas te
[David j. sheskin]_handbook_of_parametric_and_nonpNERRU
This document provides a preface and overview of the third edition of the Handbook of Parametric and Nonparametric Statistical Procedures. The handbook aims to serve as a comprehensive reference for statistical procedures, with an emphasis on practical applications over theory. It covers a wide range of univariate and bivariate statistical tests and measures of association across over 30 chapters. New material has been added to various chapters, expanding the coverage of topics like experimental design, probability, missing data techniques, and specific statistical tests.
This document discusses the different meanings and definitions of statistics. It explains that statistics has three different meanings: (1) plural sense referring to numerical facts and figures collected systematically, (2) singular sense referring to the science of collecting, analyzing, and presenting numerical data, and (3) plural of the word "statistic" referring to numerical quantities calculated from samples. The document also provides several definitions of statistics from different authors, describing it as the science of collecting, organizing, and interpreting quantitative data.
This document provides an overview of quantitative data analysis and statistical tests. It discusses research questions, variables, descriptive and inferential statistics. Common statistical tests are explained like the Mann-Whitney U test, Spearman rank correlation, Kruskal-Wallis test, t-test, Pearson correlation, ANOVA, and chi-square test. Factors to consider when selecting a statistical test are highlighted like level of data, number of groups, independent or related groups, and data distribution. The document emphasizes keeping analyses simple and statistics in context of discussion.
Statistics can be defined in both a singular and plural sense. In the singular sense, it refers to statistical methods for collecting, analyzing, and interpreting numerical data. In the plural sense, it refers to the actual numerical facts or data collected. Statistics involves systematically collecting, organizing, presenting, analyzing, and interpreting numerical data to describe features and characteristics. It allows for comparing facts, establishing relationships, and facilitating policymaking and decision making. However, statistics only studies aggregates and averages, not individual cases, and results are true only on average. It also requires properly contextualizing and referencing results.
This document provides an overview of statistical analysis for nursing research. It defines key terms like statistics, data analysis, and population. It outlines the specific objectives of understanding statistical analysis and applying it to nursing research skillfully. It also describes the various types of statistical analysis including descriptive statistics, inferential statistics, parametric and nonparametric tests. Finally, it discusses the steps in statistical analysis, available computer programs, uses of statistical analysis in different fields including nursing, and advantages and disadvantages of statistical analysis.
This document discusses statistical analysis using SPSS. It describes descriptive statistics, which present data in a usable form by describing frequency, central tendency, and dispersion. Inferential statistics make broader generalizations from samples to populations using hypothesis testing. Hypothesis testing involves research hypotheses, null hypotheses, levels of significance, and type I and II errors. Choosing an appropriate statistical test depends on the hypothesis and measurement levels of the variables. SPSS is a comprehensive system for statistical analysis that can analyze many file types and generate reports and statistics.
SPSS is a popular statistical software package that allows users to perform complex data analysis with simple instructions. It requires variables, data, measurement scales, and a code book to be defined. The document then describes different variable types (independent, dependent), measurement scales (nominal, ordinal, interval, ratio), how to start and use SPSS, and basic functions for data entry, analysis including frequencies, descriptives, correlation, and reliability which can be measured using Cronbach's alpha.
This document provides information and guidelines for students completing an econometrics project for ECON 762. It discusses acceptable topics, data sources, the required proposal and progress report, as well as formatting and content expectations for the final paper. Students must submit a 1-2 page proposal by February 13 describing their research question, data, and methods. A progress report is due April 7 to describe preliminary work and any issues encountered. The final paper should be 15-30 pages following a standard format with sections on introduction, literature review, data and methods, results, and conclusion.
This document discusses the role and importance of statistics in scientific research. It begins by defining statistics as the science of learning from data and communicating uncertainty. Statistics are important for summarizing, analyzing, and drawing inferences from data in research studies. They also allow researchers to effectively present their findings and support their conclusions. The document then describes how statistics are used and are important in many fields of scientific research like biology, economics, physics, and more. It also provides examples of statistical terms commonly used in research studies and some common misuses of statistics.
Planning the analysis and interpretation of resseaech dataramil12345
The document outlines the researcher's plan for analyzing qualitative and quantitative data collected in a study. It discusses analyzing both types of data, including describing data, identifying typical and atypical findings, and answering research questions. Methods for analyzing qualitative data include historical analysis, inductive analysis, deductive analysis, and content analysis. Quantitative data analysis relies on statistical techniques to summarize data, identify similarities and differences between groups, and test hypotheses. Common statistical analyses include descriptive analysis, univariate analysis, bivariate analysis, multivariate analysis, and comparative analysis. The document also provides guidance on choosing appropriate statistical tests based on research questions, data type, and hypotheses.
Commonly Used Statistics in Survey ResearchPat Barlow
This is a version of our "commonly used statistics" presentation that has been modified to address the commonly used statistics in survey research and analysis. It is intended to give an *overview* of the various uses of these tests as they apply to survey research questions rather than the point-and-click calculations involved in running the statistics.
This document provides an overview of quantitative analysis techniques using SPSS, including data manipulation, transformation, and cleaning methods. It also covers univariate, bivariate, and other statistical analysis methods for exploring relationships between variables and differences between groups. Specific techniques discussed include computing new variables, recoding, selecting cases, imputing missing values, aggregating data, sorting, merging files, descriptive statistics, correlations, regressions, t-tests, ANOVA, non-parametric tests, and more.
This document discusses various quantitative data analysis techniques for research. It covers describing and summarizing data, identifying relationships between variables, comparing variables, and forecasting outcomes. The five most important methods are identified as mean, standard deviation, regression, sample size determination, and hypothesis testing. Parametric and non-parametric techniques are also discussed. Four levels of data measurement are defined: nominal, ordinal, interval, and ratio data. Examples are provided for coding nominal/ordinal data and visualizing data through graphs and charts. Statistical tests like the t-test, ANOVA, and chi-square are also summarized.
This document provides an overview of data analysis and statistics concepts for a training session. It begins with an agenda outlining topics like descriptive statistics, inferential statistics, and independent vs dependent samples. Descriptive statistics concepts covered include measures of central tendency (mean, median, mode), measures of variability (range, standard deviation), and charts. Inferential statistics discusses estimating population parameters, hypothesis testing, and statistical tests like t-tests, ANOVA, and chi-squared. The document provides examples and online simulation tools. It concludes with some practical tips for data analysis like checking for errors, reviewing findings early, and consulting a statistician on analysis plans.
The document discusses various statistical tools used in research including measures of central tendency (mean, median, mode), measures of dispersion (standard deviation, interquartile range, coefficient of variation), t-tests, ANOVA, regression, correlation and more. It provides examples of when each tool would be used, such as using regression to model relationships between variables or ANOVA to test for differences between group means. The document aims to increase awareness of these common statistical tools for analyzing data in research studies across various fields.
Introduction to statistics for social sciences 1Minal Jadeja
This document provides an introduction to statistics. It defines statistics as the collection, presentation, analysis, and interpretation of numerical data. Statistics can refer to either quantitative information or a method of dealing with quantitative or qualitative information. There are two main approaches in statistics - descriptive statistics, which deals with presenting data in tables or graphs to get a general picture of a sample, and inferential statistics, which involves techniques for making inferences about a whole population based on a sample. Some key uses and applications of statistics include showing how samples differ from normal distributions, facilitating comparisons, simplifying messages in data, helping to formulate and test hypotheses, and aiding in prediction and inference. However, there are also some limitations to consider with statistics, such
Data collection and interpretation SBL1023SHAKINAZ DESA
This document provides information on data collection, analysis, interpretation, and presentation for experimental reports. It discusses analyzing data using relevant software, interpreting experimental results, discussing limitations, and using graphical and written formats to present findings. Key points include using analysis to describe, summarize, identify relationships and differences between variables, and forecast outcomes, as well as interpreting results by determining what was learned, expected, and surprising in order to draw conclusions.
This document provides an overview of key concepts for analyzing medical data from a research perspective, including:
- Statistical concepts important for medical licensing exams like scales of measurement, distributions, hypothesis testing, and study designs.
- How to determine what data is available to answer a clinical question, locate existing datasets, and analyze/interpret findings using software like Excel and SPSS.
- Resources for further learning about epidemiology, health statistics, diagnostic tests, and using statistical software.
This document discusses exploratory data analysis techniques including boxplots and five-number summaries. It explains how to organize and graph data using histograms, frequency polygons, stem-and-leaf plots, and box-and-whisker plots. The five important values used in a boxplot are the minimum, first quartile, median, third quartile, and maximum. An example constructs a boxplot for a stockbroker's daily client numbers over 11 days.
This document provides an overview of quantitative data analysis techniques used in sociology. It defines key terms like univariate analysis, bivariate analysis, and multivariate analysis. Univariate analysis examines one variable at a time through measures like frequency distributions, averages, and standard deviation. Bivariate analysis examines the relationship between two variables using cross-tabulation tables. Multivariate analysis examines relationships between multiple variables simultaneously. The document also discusses data coding, codebook construction, and ethical considerations in quantitative data analysis.
Este documento describe los conceptos clave de la organización. Explica que la organización es importante para lograr la eficiencia a través de la coordinación de recursos. También describe los diferentes tipos de recursos (humanos, materiales, técnicos) y estructuras organizacionales (lineal, funcional, lineal-funcional, staff). Además, explica conceptos como departamentalización y liderazgo que son fundamentales para la organización.
La seguridad de la información es fundamental para las administraciones públicas. El documento describe los servicios que ofrece INTECO para mejorar la seguridad, incluyendo el Centro de Respuesta a Incidentes de Seguridad (INTECO-CERT) que ayuda a pymes y ciudadanos con servicios gratuitos como detección de amenazas, formación y soporte técnico. También se mencionan las acciones de la Agrupación Empresarial Innovadora en Seguridad (AEI Seguridad) para fomentar la innovación y formación en nuevas te
Ponencia: "CONECTA, Servicios de
Integración, Seguridad y Mantenimiento de
sistemas informáticos" Ramón Basadre.
Dentro de las Jornadas de Difusión del Esquema Nacional de Seguridad Abril-Mayo 2011. XUNTA DE GALICIA-AGESTIC
Este documento describe las actuaciones de INTECO en materia de seguridad y calidad TIC. INTECO trabaja en áreas como e-Confianza, seguridad de la información, calidad del software, promoción de estándares y normalización. Ofrece servicios como el CERT para pymes y ciudadanos, la Oficina de Seguridad del Internauta, y el Centro Demostrador de Tecnologías de Seguridad. El objetivo es fomentar la confianza en las TIC y minimizar los riesgos de incidentes de seguridad.
Ponencia "INTECO y la seguridad" Fernando Gutiérrez Fernández
Secretario General de INTECO
Dentro de las Jornadas de Difusión del Esquema Nacional de Seguridad Abril-Mayo 2011. XUNTA DE GALICIA-AGESTIC
Este documento presenta un análisis FODA de una farmacia. Explica las fortalezas, oportunidades, debilidades y amenazas de la farmacia, incluyendo su ubicación, cantidad de clientes, calidad de productos y más. También describe estrategias como reducir precios, mejorar la comunicación y actualizar equipos para aprovechar oportunidades y enfrentar amenazas. El análisis concluye que identificar estas áreas puede ayudar a la farmacia a tomar mejores decisiones para mejorar.
Presentación de Paloma Llaneza, Abogado, CISA, Socio Director de Razona Legaltech y Presidenta de AEDEL (Asociación Española de Evidencias Electrónicas) “Evidencias Electrónicas” en la XIII Jornada de Seguridad TI de Nextel S.A. 2011
El documento presenta un análisis FODA de una clínica. Describe las fortalezas de la clínica como su buen servicio, doctores capacitados y atención las 24 horas. También identifica debilidades como su tamaño pequeño y falta de personal y parqueo. Las oportunidades incluyen la posibilidad de establecer más contratos con aseguradoras y agregar más especialidades aprovechando su ubicación en una zona poblada. Las amenazas son la competencia de otras clínicas cercanas.
Ponecia: "Protección de la Información"
Laura Huerta Lejo
Rpble. Dpto. Seguridad y Protección de Datos
COMPUTER-3
Dentro de las Jornadas de Difusión del Esquema Nacional de Seguridad Abril-Mayo 2011. XUNTA DE GALICIA-AGESTIC
El documento presenta una descripción detallada de los procedimientos y consideraciones para realizar estudios de seguridad y análisis de riesgo. Explica que estos estudios buscan identificar amenazas y vulnerabilidades para brindar recomendaciones de mejora, mediante la evaluación técnica de factores de riesgo, agentes generadores, y aspectos físicos e internos de las instalaciones. Asimismo, provee lineamientos sobre la recolección y análisis de información requerida para llevar a cabo dichos estudios de manera
2013 is the International Year of Statistics, a worldwide event supported by nearly 1,850 organizations.
Celebrate it with us!
Check the most important statistics books.
The document summarizes a catalog of English language books on statistics in the social sciences. It announces that 2013 was declared the International Year of Statistics by the American Statistical Association to honor the achievements of statistics in science. The catalog promotes important books in the field. It provides summaries and details of several books applying statistics and quantitative analysis in social sciences, including titles on mathematical modeling of human thought, introduction to Stata software, multivariate statistics primer, and agent-based computational sociology.
Research and Statistics Report- Estonio, Ryan.pptxRyanEstonio
Statistical tools and treatments can help researchers manage large datasets and better interpret results. Common statistical tools include measures of central tendency like the mean and measures of variability like standard deviation. Regression, hypothesis testing, and statistical software packages are also used. Determining the appropriate tools and treatments for research requires conducting a literature review, consulting experts, considering the study design, and pilot testing options.
Multivariate Approaches in Nursing Research Assignment.pdfbkbk37
The document discusses multivariate approaches used in nursing research. It discusses key variables, validity and reliability, threats to internal validity, and strengths and limitations of models used in the selected article. The document also provides an overview of different multivariate techniques including multiple regression analysis, logistic regression analysis, multivariate analysis of variance, factor analysis, and discriminant function analysis. It discusses when each technique is appropriate and how to choose the right method to solve practical problems.
The document is a catalog of English language books on medical statistics and biostatistics. It announces that 2013 was declared the International Year of Statistics by the American Statistical Association. It encourages browsing the catalog of new and interesting publications in the field. The catalog then lists and describes several books related to topics in medical statistics and biostatistics.
Lang T, Altman D. Statistical Analyses and Methods in the Publ.docxDIPESH30
Lang T, Altman D. Statistical Analyses and Methods in the Published Literature: the SAMPL Guidelines.
1
Basic Statistical Reporting for
Articles Published in Biomedical Journals:
The “Statistical Analyses and Methods
in the Published Literature” or
The SAMPL Guidelines”
Thomas A. Lang
a
and Douglas G. Altman
b
a
Principal, Tom Lang Communications and Training International
b
Director, Centre for Statistics in Medicine, Oxford University
Have they reflected that the sciences founded on observation can only be promoted by
statistics? . . . If medicine had not neglected this instrument, this means
of progress, it would possess a greater number of positive truths, and
stand less liable to the accusation of being a science of unfixed
principles, vague and conjectural.
Jean-Etienne Dominique Esquirol, an early French psychiatrist,
quoted in The Lancet, 1838 [1]
Introduction
The first major study of the quality of statistical
reporting in the biomedical literature was published
in 1966 [2]. Since then, dozens of similar studies
have been published, every one of which has found
that large proportions of articles contain errors in the
application, analysis, interpretation, or reporting of
statistics or in the design or conduct of research. (See,
for example, references 3 through 19.) Further, large
proportions of these errors are serious enough to call
the authors’ conclusions into question [5,18,19]. The
problem is made worse by the fact that most of these
studies are of the world’s leading peer-reviewed
general medical and specialty journals.
Although errors have been found in more complex
statistical procedures [20,21,22], paradoxically, many
Lang T, Altman D. Basic statistical reporting for
articles published in clinical medical journals: the
SAMPL Guidelines. In: Smart P, Maisonneuve H,
Polderman A (eds). Science Editors' Handbook,
European Association of Science Editors, 2013. This
document may be reprinted without charge but must
include the original citation.
errors are in basic, not advanced, statistical methods
[23]. Perhaps advanced methods are suggested by
consulting statisticians, who then competently
perform the analyses, but it is also true that authors
are far more likely to use only elementary statistical
methods, if they use any at all [23-26]. Still, articles
with even major errors continue to pass editorial and
peer review and to be published in leading journals.
The truth is that the problem of poor statistical
reporting is long-standing, widespread, potentially
serious, concerns mostly basic statistics, and yet is
largely unsuspected by most readers of the
biomedical literature [27].
More than 30 years ago, O’Fallon and colleagues
recommended that “Standards governing the content
and format of statistical aspects should be developed
to guide authors in the preparation of manuscripts”
[28] ...
Statistics are used by organizations to measure and analyze business performance. American Express uses statistics such as total returns to shareholders, numbers of cardholders by age group, and cardholder spending by age to analyze business units, identify targeted customer groups, and inform marketing campaigns. Statistics on labor force characteristics by gender help conclude that male monthly incomes are typically higher than females, though this does not necessarily mean males spend more.
Systematic review article and meta analysis .main steps for successful writin...Pubrica
This document provides guidance on writing systematic review and meta-analysis articles. It outlines 7 main steps: 1) defining clear objectives, 2) developing focused research questions, 3) obtaining relevant data sources through literature searches, 4) establishing selection criteria, 5) collecting data, 6) interpreting and reporting results, and 7) drawing conclusions. It also describes how meta-analyses aggregate effect sizes from multiple studies to assess the overall magnitude of an effect. Follow a systematic process and clearly explain any deviations from normal methods.
This book provides a comprehensive overview of modern statistical methods aimed at overcoming issues that arise when standard statistical assumptions like normality and equal variance are violated. It introduces robust techniques for estimating location, testing hypotheses, computing confidence intervals, comparing groups, detecting outliers, and linear regression. The book is intended to bridge the gap between current robust method developments and practical application, offering an intuitive understanding of why and how standard techniques can mislead and the advantages of modern robust alternatives. It assumes a basic understanding of statistical concepts and methods.
This document provides information about the authors, publisher, and production team of a statistics textbook. It summarizes the book's contents and goals in teaching applied statistics and probability concepts at an introductory level for engineering students. Key details include the modest mathematical approach aimed for a one-semester course, examples drawn from real engineering data, and coverage of topics like modeling, experiment design, and process monitoring.
Application Of Sampling Methods For The Research DesignGina Rizzo
This document discusses sampling methods and sample size considerations for research design. It explains that sampling involves selecting a representative subset of a larger population for study. The sample size depends on factors like the population size, desired precision of results, level of analysis required, and practical constraints. Quantitative research typically uses larger sample sizes while qualitative research uses smaller, in-depth samples. Sample size impacts statistical precision, with larger samples decreasing sampling error. The document provides guidance on determining appropriate sample sizes for different types of studies.
Journal Club - Best Practices for Scientific ComputingBram Zandbelt
This document discusses the importance of best practices in scientific computing. It notes that scientists rely heavily on software for research, with many writing their own code. However, most scientists are self-taught in software skills and may be unaware of best practices that could help them write more reliable and maintainable code. The document advocates treating software like a scientific instrument and following practices such as version control, testing, and automation. Adopting these practices could help reduce errors and make software easier to reuse.
Graphs represent data in an engaging manner and make c.docxshericehewat
Graphs represent data in an engaging manner and make comparisons and analyses easier. For example, a graph depicting the number of crimes committed each year over a decade is easier to comprehend visually than reading the numerical values for each year. Before creating a graph, however, it is important to choose one that appropriately represents the data. A histogram, rather than a pie chart, is appropriate for depicting the age groups (e.g., 15–24, 25–34) of murder victims in a city. Histograms are designed to be used with variables that are categorized, but pie charts plot each value. Therefore, it would be easier to read a histogram showing bars for age groups of murder victims than a pie chart in which every single age would have to be plotted. In the past, creating graphs was cumbersome and time consuming, but present-day software programs such as Microsoft Word and Excel provide tutorials that walk you through the process. With knowledge of these software programs, you can create customized charts and figures to represent your research data in visually interesting ways. In this Assignment, you create at least two different graphs in Excel or Word that can be used to illustrate hypothetical data related to six incidents of crime.
· Create at least two different graphs in Excel or Word using the data provided in the table below:
Type of Crime
Offender’s Age
(Years)
Offender’s Gender
Time of the Incident
Theft
22
Male
Early morning
Possession of drugs
21
Female
Late evening
Theft
19
Male
Late evening
Theft
33
Female
Afternoon
Possession of drugs
47
Female
Morning
Possession of drugs
17
Male
Early morning
· Briefly describe the data represented in the graphs and/or charts you created.
· Explain why the graphs and/or charts you created best represent the data compared to other options. Be specific.
Submit the graphs you created in a document that is separate from your written Assignment.
Bachman, R. D., & Schutt, R. K. (2019). The practice of research in criminology and criminal justice (7th ed.). Thousand Oaks, CA: SAGE Publications.
· Chapter 4, “Conceptualization and Measurement” (pp. 86–116)
The Practice of Research in Criminology and Criminal Justice, 7th Edition by Bachman, R. D. & Schutt, R. K. Copyright 2019 by SAGE Publications, Inc. Reprinted by permission of SAGE Publications, Inc via the Copyright Clearance Center.
Bachman, R. D., & Schutt, R. K. (2019). The practice of research in criminology and criminal justice (7th ed.). Thousand Oaks, CA: SAGE Publications.
· Chapter 14, “Analyzing Quantitative Data” (pp. 404–415 and 426–444)
The Practice of Research in Criminology and Criminal Justice, 7th Edition by Bachman, R. D. & Schutt, R. K. Copyright 2019 by SAGE Publications, Inc. Reprinted by permission of SAGE Publications, Inc via the Copyright Clearance Center.
Trochim, W. M. K. (2006). Levels of measurement. In Research methods knowledge base. Retrieved from http://www.socialresearchmethods.net/kb/measlevl.php
Walden Univer ...
Identify the types of graphsand statistics that areapproprMalikPinckney86
This chapter introduces descriptive and inferential statistics that are commonly used in social research. Descriptive statistics describe the distribution of and relationships among variables, and include frequency distributions, measures of central tendency and variation, graphs, and reliability tests. Inferential statistics estimate the degree of confidence in generalizing sample results to the population by considering concepts like confidence intervals. The chapter uses data from a study of delinquency causes among high school students to demonstrate statistical techniques.
This document provides an overview and introduction to the statistical software R. It describes how R can be obtained and installed. R is a free and open-source software environment for statistical analysis and graphics. The document outlines the basic features of the R environment, including how to work with data and packages in R. It provides a conceptual overview of the organization of the book, which uses R and biological examples to teach statistics concepts ranging from basic to advanced topics.
The document provides information about the syllabus for the Data Analytics (KIT-601) course. It includes 5 units that will be covered: Introduction to Data Analytics, Data Analysis techniques including regression modeling and multivariate analysis, Mining Data Streams, Frequent Itemsets and Clustering, and Frameworks and Visualization. It lists the course outcomes and Bloom's taxonomy levels. It also provides details on the topics to be covered in each unit, including proposed lecture hours, textbooks, and an evaluation scheme. The syllabus aims to discuss concepts of data analytics and apply techniques such as classification, regression, clustering, and frequent pattern mining on data.
Running head INSERT TITLE HERE1INSERT TITLE HERE4.docxjeanettehully
Running head: INSERT TITLE HERE 1
INSERT TITLE HERE 4
Insert Title Here
Insert Your Name Here
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Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regression analysis, and multiple regression analysis using the correlation tab, simple regression tab, and multiple regression tab respectively. The statistical output tables should be cut and pasted from Excel directly into the final project document. For the regression hypotheses, display and discuss the predictive regression equations.
Correlation: Hypothesis Testing
Restate the hypotheses:
Example:
Ho1: There is no statistically significant relationship between height and weight.
Ha1:There is a statistically significant relationship between height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below the Excel output. Your explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null hypothesis and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a moderately strong positive correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables.
Using an alpha of .05, the results indicate a p value of .023 < .05. Therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted that there is a statistically significant relationship between height and weight.
Note: Excel data analysis Toolpak does not automatically calculate the p value when using the correlation function. As a workaround, the data should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function.
Simple Regression: Hypothesis Testing
Restate the hypotheses:
Ho2:
Ha2:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R square, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation.
Multiple Regression: Hypothesis Testing
Restate the hypotheses:
Ha3:
Ha3:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R square, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, and the regression model as an equation with explanation.
References
Include references here using hanging indentations. Remember to remove this example.
Creswell, J. W., & ...
Unit III - Statistical Process Control (SPC)Dr.Raja R
The seven tools of quality – Statistical Fundamentals – Measures of central Tendency and Dispersion, Population and Sample, Normal Curve, Control Charts for variables Xbar and R chart and attributes P, nP, C, and u charts, Industrial Examples, Process capability, Concept of six sigma – New seven Management tools.
This document provides templates and guidelines for writing research proposals and conducting action research. It discusses key components of a research proposal, including an introduction, literature review, research questions, methodology, work plan, cost estimates, and references. The methodology section provides details on sampling, data collection, ethical issues, and data analysis. Quantitative and qualitative research methods are also compared. The document provides information on research designs, variables, and common statistical tests used in data analysis.
Alexander Street Products is a leading provider of streaming academic video and music to libraries. They have:
- The largest collection of academic video with over 50,000 titles across many disciplines.
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- Their flagship video offering, Academic Video Online, now allows libraries to own their choice of films and hosts libraries' own video content for free.
IHS provides technical knowledge collections that allow users to efficiently find information from a variety of authoritative sources. Their platform combines search technologies with over 57 million documents from standards organizations, publishers, patents and proprietary sources. This comprehensive solution is designed to help engineers solve problems faster by simplifying information management.
This document provides summaries of books related to various areas of law, including administrative law, arbitration, company law, comparative law, competition law, and constitutional law. For each book, it lists the title, publication date, format (hardcover or softcover), price in British pounds, and a brief 1-3 sentence description of what the book is about. The books appear to have been sourced from various academic publishers like Europa Law, Oxford University Press, and other university presses.
Prezentacja "Uniwersytet im. Adama Mickiewicza w Poznaniu – partner do współpracy z gospodarką" autorstwa Prof. UAM dr hab. Marka Nawrockiego Prorektora ds. informatyzacji i współpracy z gospodarką przedstawia relacje Uniwersytetu z otoczeniem oraz ofertę sierowaną do przedsiębiorstw.
Cale Carmichael, przedstawiciel firmy IHS, zaprezentował uczestnikom Seminarium "Informacja naukowa i techniczna w planowaniu oraz realizacji badań i wdrożeń projektów przemysłowych", które odbyło się 4 czerwca 2014 roku w Poznaniu, narzędzia do kompleksowego zarządzania dokumentami technicznymi, które pozwala na cięcie kosztów, zmniejszenie ryzyka oraz poprawę procesów pracy.
Prezentacja wygłoszona przez wiceprezesa firmy ABE-IPS Grzegorza Majerowicza. Jej celem było przybliżenie uczestnikowm Seminarium "Informacja naukowa i techniczna w planowaniu oraz realizacji badań i wdrożeń projektów przemysłowych", które odbyło się 4 czerwca 2014 roku w Poznaniu, firmy ABE-IPS oraz oferowanych przez nią narzędzi wspierających rozwój innowacyjności przedsiębiorstw.
Prezentacja pod tytułem "Dostęp do najnowszych wymagań technicznych i środowiskowych oraz monitoring rynków docelowych, jako czynniki wpływające na wzrost konkurencyjności polskich przedsiębiorstw" została wygłoszona przez Krzysztofa Kowalczyka podczas Seminarium "Informacja naukowa i techniczna w planowaniu oraz realizacji badań i wdrożeń projektów przemysłowych", które odbyło się 4 czerwca 2014 roku w Poznaniu.
Prezentacja pod tytułem "Poznański Model Transferu Wiedzy" wygłoszona przez Prof. UAM dr hab. inż. Hieronima Maciejewskiego podczas Seminarium "Informacja naukowa i techniczna w planowaniu oraz realizacji badań i wdrożeń projektów przemysłowych", które odbyło się 4 czerwca 2014 roku w Poznaniu.
The European Brain Council pledged to make 2014 the European Year of the Brain.
Celebrate with us this event and check our offer
Rok 2014 ogłoszono Europejskim Rokiem Mózgu.
Jak dowodzi Europejska Rada Mózgu: zrozumienie funkcjonowania mózgu może przyczynić się do odkrycia nowych sposobów leczenia, a także zapobiegania chorobom takim jak stwardnienie rozsiane, Parkinson czy Alzheimer.
To także okazja to propagowania wiedzy na ten temat.
The European Brain Council pledged to make 2014 the European Year of the Brain.
Celebrate with us this event and check our offer.
Rok 2014 ogłoszono Europejskim Rokiem Mózgu.
Jak dowodzi Europejska Rada Mózgu: zrozumienie funkcjonowania mózgu może przyczynić się do odkrycia nowych sposobów leczenia, a także zapobiegania chorobom takim jak stwardnienie rozsiane, Parkinson czy Alzheimer.
To także okazja to propagowania wiedzy na ten temat.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
Azure Interview Questions and Answers PDF By ScholarHat
General Statistics
1. Katalog książek
anglojęzycznych
statystyka ogólna
Amerykańskie Towarzystwo Statystyczne ogłosiło rok 2013
Międzynarodowym Rokiem Statystyki. Ogólnoświatowa akcja
ma na celu uczczenie i docenienie osiągnięć nauk statystycznych.
Przyłączyliśmy się do akcji promując najważniejsze książki z tej
dziedziny.
Przeglądaj katalog z nowościami i najciekawszymi publikacjami.
Dowiedz się więcej na www.abe.pl/statystyka2013
2.
Statystyka ogólna
2 www.abe.pl
A Career in Statistics: Beyond the
Numbers
9780470404416
22.07.2011
Oprawa: miękka
£ 46,95
Gerald J. Hahn
A valuable guide to a successful career as a statistician A Career in Statistics:
Beyond the Numbers prepares readers for careers in statistics by emphasizing
essential concepts and practices beyond the technical tools provided in standard
courses and texts. This insider's guide from internationally recognized applied
statisticians helps readers decide whether a career in statistics is right for them,
provides hands-on guidance on how to prepare for such a career, and shows how
to succeed on the job. The book provides non-technical guidance for a successful
career. The authors' extensive industrial experience is supplemented by insights
from contributing authors from government and academia, Carol Joyce Blumberg,
Leonard M. Gaines, Lynne B. Hare, William Q. Meeker, and Josef Schmee.
Following an introductory chapter that provides an overview of the field, the authors
discuss the various dimensions of a career in applied statistics in three succinct
parts: The Work of a Statistician describes the day-to-day activities of applied
statisticians in business and industry, official government, and various other
application areas, highlighting the work environment and major on-the-job
Wiley
...
A Course in Probability
9780321189547
01.08.2003
Oprawa: miękka
£ 50,99
Neil A. Weiss
This text is intended primarily for a first course in mathematical probability for
students in mathematics, statistics, operations research, engineering, and computer
science. It is also appropriate for mathematically oriented students in the physical
and social sciences. Prerequisite material consists of basic set theory and a firm
foundation in elementary calculus, including infinite series, partial differentiation, and
multiple integration. Some exposure to rudimentary linear algebra (e.g., matrices and
determinants) is also desirable. This text includes pedagogical techniques not often
found in books at this level, in order to make the learning process smooth, efficient,
and enjoyable.
Pearson Education
A First Course in Bayesian Statistical
Methods
9780387922997
15.06.2009
Oprawa: twarda
€ 59,95
Peter D. Hoff
A self-contained introduction to probability, exchangeability and Bayes' rule provides
a theoretical understanding of the applied material. Numerous examples with R-
code that can be run "as-is" allow the reader to perform the data analyses
themselves. The development of Monte Carlo and Markov chain Monte Carlo
methods in the context of data analysis examples provides motivation for these
computational methods.
Springer
A First Course in Probability
9780321866813
02.01.2013
Oprawa: miękka
£ 52,99
Sheldon M. Ross
A First Course in Probability, Ninth Edition, features clear and intuitive explanations
of the mathematics of probability theory, outstanding problem sets, and a variety of
diverse examples and applications. This book is ideal for an upper-level
undergraduate or graduate level introduction to probability for math, science,
engineering and business students. It assumes a background in elementary
calculus.
Pearson Education
A Whistle-Stop Tour of Statistics
9781439877487
16.01.2012
Oprawa: miękka
£ 26,99
Brian S. Everitt
A Whistle-Stop Tour of Statistics introduces basic probability and statistics through
bite-size coverage of key topics. A review aid and study guide for undergraduate
students, it presents descriptions of key concepts from probability and statistics in
self-contained sections. Features Presents an accessible reference to the key
concepts in probability and statistics Introduces each concept through bite-size
descriptions and presents interesting real-world examples Includes lots of diagrams
and graphs to clarify and illustrate topics Provides a concise summary of ten major
areas of statistics including survival analysis and the analysis of longitudinal data
Written by Brian S, Everitt, the author of over 60 statistical texts, the book shows
how statistics can be applied in the real world, with interesting examples and plenty
of diagrams and graphs to illustrate concepts.
Taylor & Francis
Adaptive Tests of Significance Using
Permutations of Residuals with R and SAS
9780470922255
30.03.2012
Oprawa: twarda
£ 83,50
Thomas W. O'Gorman
Adaptive Tests of Significance Using Permutations of Residuals with R and SAS
illustrates the power of adaptive tests and showcases their ability to adjust the
testing method to suit a particular set of data. The book utilizes state-of-the-art
software to demonstrate the practicality and benefits for data analysis in various
fields of study.
Beginning with an introduction, the book moves on to explore the underlying
concepts of adaptive tests, including:
Smoothing methods and normalizing transformations
Permutation tests with linear methods
Applications of adaptive tests
Multicenter and cross-over trials
Analysis of repeated measures data
Adaptive confidence intervals and estimates
Wiley
3.
Statystyka ogólna
www.abe.pl 3
Advances in Statistical Monitoring of
Complex Multivariate Processes
9780470028193
14.09.2012
Oprawa: twarda
£ 55,00
Uwe Kruger
The development and application of multivariate statistical techniques in process
monitoring has gained substantial interest over the past two decades in academia
and industry alike. Initially developed for monitoring and fault diagnosis in complex
systems, such techniques have been refined and applied in various engineering
areas, for example mechanical and manufacturing, chemical, electrical and
electronic, and power engineering. The recipe for the tremendous interest in
multivariate statistical techniques lies in its simplicity and adaptability for developing
monitoring applications. In contrast, competitive model, signal or knowledge based
techniques showed their potential only whenever cost-benefit economics have
justified the required effort in developing applications. Statistical Monitoring of
Complex Multivariate Processes presents recent advances in statistics based
process monitoring, explaining how these processes can now be used in areas
such as mechanical and manufacturing engineering for example, in addition to the
traditional chemical industry. This book: Contains a detailed theoretical background
of the component technology.
Wiley
An Introduction to Applied Multivariate
Analysis with R
9781441996497
28.04.2011
Oprawa: miękka
€ 49,95
Brian S. Everitt
The majority of data sets collected by researchers in all disciplines are multivariate,
meaning that several measurements, observations, or recordings are taken on each
of the units in the data set. These units might be human subjects, archaeological
artifacts, countries, or a vast variety of other things. In a few cases, it may be
sensible to isolate each variable and study it separately, but in most instances all the
variables need to be examined simultaneously in order to fully grasp the structure
and key features of the data. For this purpose, one or another method of
multivariate analysis might be helpful, and it is with such methods that this book is
largely concerned. Multivariate analysis includes methods both for describing and
exploring such data and for making formal inferences about them. The aim of all the
techniques is, in general sense, to display or extract the signal in the data in the
presence of noise and to find out what the data show us in the midst of their
apparent chaos.
Springer
An Introduction to Bootstrap Methods
with Applications to R
9780470467046
02.12.2011
Oprawa: twarda
£ 66,95
Michael R. Chernick
A comprehensive introduction to bootstrap methods in the R programming
environment Bootstrap methods provide a powerful approach to statistical data
analysis, as they have more general applications than standard parametric methods.
An Introduction to Bootstrap Methods with Applications to R explores the
practicality of this approach and successfully utilizes R to illustrate applications for
the bootstrap and other resampling methods. This book provides a modern
introduction to bootstrap methods for readers who do not have an extensive
background in advanced mathematics. Emphasis throughout is on the use of
bootstrap methods as an exploratory tool, including its value in variable selection
and other modeling environments. The authors begin with a description of
bootstrap methods and its relationship to other resampling methods, along with an
overview of the wide variety of applications of the approach. Subsequent chapters
offer coverage of improved confidence set estimation, estimation of error rates in
discriminant analysis, and applications to a wide variety of hypothesis testing and
estimation problems, including pharmaceutical, genomics, and economics.
Wiley
An Introduction to Statistics: An Active
Learning Approach
9781452217437
02.03.2013
Oprawa: miękka
£ 39,99
Kieth A. Carlson
In An Introduction to Statistics Kieth Carlson and Jennifer Winquist encourage an
active approach to learning statistics. While the chapters in this book introduce
basic and key concepts, this book is unique in the depth of its active pedagogical
approach. Carefully placed reading questions throughout each chapter reinforce
difficult concepts and guide student learning: 29 in-depth activities, each
accompanied by learning objectives, carefully developed scenarios, problem sets,
and quiz questions give students the opportunity to test or demonstrate their
understanding of basic concepts while they read detailed explanations of more
complex statistical concepts; and 15 sets of practice problems further solidify
student learning. When using most traditional text books, students only perform
statistical procedures after they read multiple pages of text. This book adopts a
workbook approach that forces students to be actively engaged while they read
explanations. Most of the activities are self-correcting so if students misunderstand
a concept their misunderstanding is corrected early in the learning process.
SAGE
Analysis of International Large-Scale
Assessment Data
9781439895122
15.10.2013
Oprawa: twarda
£ 49,99
Leslie Rutkowski
International large-scale assessments (ILSAs) of educational achievement such as
the Trends in International Mathematics and Science Study and the Programme for
International Student Assessment are an increasingly important part of the
educational research and policy landscape in the U.S. and internationally. This book
will bring together recognized scholars in the field of ILSA, behavioral statistics, and
policy to develop a detailed guide for ILSA users that goes beyond ILSA user
manuals.
Taylor & Francis
ANOVA and ANCOVA: A GLM Approach
9780470385555
28.10.2011
Oprawa: twarda
£ 73,50
Andrew Rutherford
Provides an in-depth treatment of ANOVA and ANCOVA techniques from a linear
model perspective ANOVA and ANCOVA: A GLM Approach provides a
contemporary look at the general linear model (GLM) approach to the analysis of
variance (ANOVA) of one- and two-factor psychological experiments. With its
organized and comprehensive presentation, the book successfully guides readers
through conventional statistical concepts and how to interpret them in GLM terms,
treating the main single- and multi-factor designs as they relate to ANOVA and
ANCOVA. The book begins with a brief history of the separate development of
ANOVA and regression analyses, and then goes on to demonstrate how both
analyses are incorporated into the understanding of GLMs. This new edition now
explains specific and multiple comparisons of experimental conditions before and
after the Omnibus ANOVA, and describes the estimation of effect sizes and power
analyses leading to the determination of appropriate sample sizes for experiments to
be conducted.
Wiley
4.
Statystyka ogólna
4 www.abe.pl
Applied Categorical and Count Data
Analysis
9781439806241
04.07.2012
Oprawa: twarda
£ 57,99
Wan Tang
Developed from the authors' graduate-level biostatistics course, Applied Categorical
and Count Data Analysis explains how to perform the statistical analysis of discrete
data, including categorical and count outcomes. The authors describe the basic
ideas underlying each concept, model, and approach to give readers a good grasp
of the fundamentals of the methodology without using rigorous mathematical
arguments. The text covers classic concepts and popular topics, such as
contingency tables, logistic models, and Poisson regression models, along with
modern areas that include models for zero-modified count outcomes, parametric
and semiparametric longitudinal data analysis, reliability analysis, and methods for
dealing with missing values. R, SAS, SPSS, and Stata programming codes are
provided for all the examples, enabling readers to immediately experiment with the
data in the examples and even adapt or extend the codes to fit data from their own
studies. Designed for a one-semester course for graduate and senior
undergraduate students in biostatistics, this self-contained text is also suitable as a
self-learning guide for biomedical and psychosocial researchers.
Taylor & Francis
Applied Multivariate Statistical Analysis
9780135143506
30.04.2007
Oprawa: miękka
£ 68,99
Richard A. Johnson
For courses in Multivariate Statistics, Marketing Research, Intermediate Business
Statistics, Statistics in Education, and graduate-level courses in Experimental Design
and Statistics. Appropriate for experimental scientists in a variety of disciplines, this
market-leading text offers a readable introduction to the statistical analysis of
multivariate observations. Its primary goal is to impart the knowledge necessary to
make proper interpretations and select appropriate techniques for analyzing
multivariate data. Ideal for a junior/senior or graduate level course that explores the
statistical methods for describing and analyzing multivariate data, the text assumes
two or more statistics courses as a prerequisite.
Pearson Education
Applied Multivariate Statistical Analysis
9783642172281
01.12.2011
Oprawa: miękka
€ 79,95
Wolfgang Karl Hardle
Most of the observable phenomena in the empirical sciences are of a multivariate
nature. In financial studies, assets are observed simultaneously and their joint
development is analysed to better understand general risk and to track indices. In
medicine recorded observations of subjects in different locations are the basis of
reliable diagnoses and medication. In quantitative marketing consumer preferences
are collected in order to construct models of consumer behavior. The underlying
data structure of these and many other quantitative studies of applied sciences is
multivariate. Focusing on applications this book presents the tools and concepts of
multivariate data analysis in a way that is understandable for non-mathematicians
and practitioners who need to analyze statistical data. The book surveys the basic
principles of multivariate statistical data analysis and emphasizes both exploratory
and inferential statistics. All chapters have exercises that highlight applications in
different fields.
Springer
Applied Regression Modeling
9781118097281
17.08.2012
Oprawa: twarda
£ 73,50
Iain Pardoe
This book offers a practical, concise introduction to regression analysis for upper-
level undergraduate students of diverse disciplines including, but not limited to
statistics, the social and behavioral sciences, MBA, and vocational studies. The
book's overall approach is strongly based on an abundant use of illustrations,
examples, case studies, and graphics. It emphasizes major statistical software
packages, including SPSS(r), Minitab(r), SAS(r), R, and R/S-PLUS(r). Detailed
instructions for use of these packages, as well as for Microsoft Office Excel(r), are
provided on a specially prepared and maintained author web site. Select software
output appears throughout the text. To help readers understand, analyze, and
interpret data and make informed decisions in uncertain settings, many of the
examples and problems use real-life situations and settings. The book introduces
modeling extensions that illustrate more advanced regression techniques, including
logistic regression, Poisson regression, discrete choice models, multilevel models,
Bayesian modeling, and time series and forecasting.
Wiley
Applied Time Series Analysis
9781439818374
24.10.2011
Oprawa: twarda
£ 60,99
Wayne A. Woodward
Virtually any random process developing chronologically can be viewed as a time
series. In economics, closing prices of stocks, the cost of money, the jobless rate,
and retail sales are just a few examples of many. Developed from course notes and
extensively classroom-tested, Applied Time Series Analysis includes examples
across a variety of fields, develops theory, and provides software to address time
series problems in a broad spectrum of fields. The authors organize the information
in such a format that graduate students in applied science, statistics, and
economics can satisfactorily navigate their way through the book while maintaining
mathematical rigor. One of the unique features of Applied Time Series Analysis is the
associated software, GW-WINKS, designed to help students easily generate
realizations from models and explore the associated model and data characteristics.
The text explores many important new methodologies that have developed in time
series, such as ARCH and GARCH processes, time varying frequencies (TVF),
wavelets, and more.
Taylor & Francis
Arthur L. Bowley: A Pioneer in Modern
Statistics and Economics
9789812835505
16.04.2011
Oprawa: twarda
£ 72,00
Samuel Kotz
Arthur Lyon Bowley, the founding father of modern statistics, was an important and
colorful figure and a leader in cementing the foundations of statistical methodology,
including survey methodology, and of the applications of statistics to economical
and social issues during the late 19th and early 20th centuries. In many respects, he
was ahead of his time.The giants in this field around that time were largely
concentrated in the British Isles and Scandinavian countries; among these
contributors, Arthur Bowley was one of the most active in revolutionizing statistical
methodology and its economic applications. However, Bowley has been vastly
undervalued by subsequent commentators - while hundreds of articles and books
have been written on Karl Pearson, those on Arthur Bowley amount to a dozen or
less. This book seeks to remedy this and fill in an important omission in the
monographical literature on the history of statistics. In particular, the recent
resurgence of interest in poverty research has led to a renewed interest in Bowley's
legacy.
World Scientific Publishing
5.
Statystyka ogólna
www.abe.pl 5
Assessment Methods in Statistical
Education
9780470745328
25.03.2010
Oprawa: miękka
£ 57,50
Neville Hunt
Assessment Methods in Statistical Education: An International Perspective provides
a modern, international perspective on assessing students of statistics in higher
education. It is a collection of contributions written by some of the leading figures in
statistical education from around the world, drawing on their personal teaching
experience and educational research. The book reflects the wide variety of
disciplines, such as business, psychology and the health sciences, which include
statistics teaching and assessment. The authors acknowledge the increasingly
important role of technology in assessment, whether it be using the internet for
accessing information and data sources or using software to construct and manage
individualised or online assessments. Key Features: Presents successful
assessment strategies, striking a balance between formative and summative
assessment, individual and group work, take-away assignments and supervised
tests. Assesses statistical thinking by questioning students' ability to interpret and
communicate the results of their analysis. Relates assessment to the real world by
basing it on real data in an appropriate context.
Wiley
Basic and Advanced Bayesian
Structural Equation Modeling
9780470669525
24.08.2012
Oprawa: twarda
£ 65,00
Sik-Yum Lee
Basic and Advanced Structural Equation Models for Medical and Behavioural
Sciences introduces the Bayesian approach to SEMs, including the selection of prior
distributions and data augmentation, and offers an overview of the subject's recent
advances. This book takes a Bayesian approach to SEMs allowing the use of prior
information resulting in improved parameter estimates, latent variable estimates, and
statistics for model comparison, as well as offering more reliable results for smaller
samples.
Wiley
Basic Statistical Tools for Improving
Quality
9780470889497
20.05.2011
Oprawa: miękka
£ 36,95
Chang W. Kang
This book is an introductory book on improving the quality of a process or a system,
primarily through the technique of statistical process control (SPC). There are
numerous technical manuals available for SPC, but this book differs in two ways: (1)
the basic tools of SPC are introduced in a no-nonsense, simple, non-math manner,
and (2) the methods can be learned and practiced in an uncomplicated fashion
using free software (eZ SPC 2.0), which is available to all readers online as a
downloadable product. The book explains QC7 Tools, control charts, and statistical
analysis including basic design of experiments. Theoretical explanations of the
analytical methods are avoided; instead, results are interpreted through the use of
the software.
Wiley
Bayesian Analysis of Stochastic
Process Models
9780470744536
30.03.2012
Oprawa: twarda
£ 60,00
Fabrizio Ruggeri
Bayesian analysis of complex models based on stochastic processes has in recent
years become a growing area. This book provides a unified treatment of Bayesian
analysis of models based on stochastic processes, covering the main classes of
stochastic processing including modeling, computational, inference, forecasting,
decision making and important applied models. Key features: Explores Bayesian
analysis of models based on stochastic processes, providing a unified treatment.
Provides a thorough introduction for research students. Computational tools to deal
with complex problems are illustrated along with real life case studies Looks at
inference, prediction and decision making. Researchers, graduate and advanced
undergraduate students interested in stochastic processes in fields such as
statistics, operations research (OR), engineering, finance, economics, computer
science and Bayesian analysis will benefit from reading this book. With numerous
applications included, practitioners of OR, stochastic modelling and applied
statistics will also find this book useful.
Wiley
Bayesian Ideas and Data Analysis
9781439803547
06.07.2010
Oprawa: twarda
£ 48,99
Ronald Christensen
Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and
Data Analysis: An Introduction for Scientists and Statisticians presents statistical
tools to address scientific questions. It highlights foundational issues in statistics, the
importance of making accurate predictions, and the need for scientists and
statisticians to collaborate in analyzing data. The WinBUGS code provided offers a
convenient platform to model and analyze a wide range of data. The first five
chapters of the book contain core material that spans basic Bayesian ideas,
calculations, and inference, including modeling one and two sample data from
traditional sampling models. The text then covers Monte Carlo methods, such as
Markov chain Monte Carlo (MCMC) simulation. After discussing linear structures in
regression, it presents binomial regression, normal regression, analysis of variance,
and Poisson regression, before extending these methods to handle correlated data.
The authors also examine survival analysis and binary diagnostic testing. A
complementary chapter on diagnostic testing for continuous outcomes is available
on the book's website.
Taylor & Francis
Bayesian Methods: A Social and
Behavioral Sciences Approach
9781439862483
15.06.2013
Oprawa: twarda
£ 48,99
Jeff Gill
This updated, bestselling book continues to be one of the only Bayesian statistics
texts designed for social scientists. Incorporating new research and additional
material, the third edition presents state-of-the-art guidance on Bayesian statistical
computing. It emphasizes Markov chain Monte Carlo (MCMC) and computation with
R and WinBUGS. Along with doubling the number of exercises, this edition covers
time series, decision theory, nonparametric models, and mixture models. A solutions
manual is available with qualifying course adoption.
Taylor & Francis
6.
Statystyka ogólna
6 www.abe.pl
Bayesian Model Selection and
Statistical Modeling
9781439836149
03.06.2010
Oprawa: twarda
£ 62,99
Tomohiro Ando
Bayesian model selection is a fundamental part of the Bayesian statistical modeling
process. The quality of these solutions usually depends on the goodness of the
constructed Bayesian model. Realizing how crucial this issue is, many researchers
and practitioners have been extensively investigating the Bayesian model selection
problem. This book provides comprehensive explanations of the concepts and
derivations of the Bayesian approach for model selection and related criteria,
including the Bayes factor, the Bayesian information criterion (BIC), the generalized
BIC, and the pseudo marginal likelihood. It also includes a wide range of practical
examples of model selection criteria.
Taylor & Francis
Bayesian Nonparametrics
9780521513463
12.04.2010
Oprawa: twarda
£ 42,00
Nils Lid Hjort
Bayesian nonparametrics works - theoretically, computationally. The theory provides
highly flexible models whose complexity grows appropriately with the amount of
data. Computational issues, though challenging, are no longer intractable. All that is
needed is an entry point: this intelligent book is the perfect guide to what can seem
a forbidding landscape. Tutorial chapters by Ghosal, Lijoi and Prunster, Teh and
Jordan, and Dunson advance from theory, to basic models and hierarchical
modeling, to applications and implementation, particularly in computer science and
biostatistics. These are complemented by companion chapters by the editors and
Griffin and Quintana, providing additional models, examining computational issues,
identifying future growth areas, and giving links to related topics. This coherent text
gives ready access both to underlying principles and to state-of-the-art practice.
Specific examples are drawn from information retrieval, NLP, machine vision,
computational biology, biostatistics, and bioinformatics.
Cambridge University Press
Bayesian Statistics: An Introduction
9781118332573
03.08.2012
Oprawa: miękka
£ 35,00
Peter M. Lee
Bayesian Statistics is the school of thought that combines prior beliefs with the
likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter
Lee's book appeared in 1989, but the subject has moved ever onwards, with
increasing emphasis on Monte Carlo based techniques. This new fourth edition
looks at recent techniques such as variational methods, Bayesian importance
sampling, approximate Bayesian computation and Reversible Jump Markov Chain
Monte Carlo (RJMCMC), providing a concise account of the way in which the
Bayesian approach to statistics develops as well as how it contrasts with the
conventional approach. The theory is built up step by step, and important notions
such as sufficiency are brought out of a discussion of the salient features of specific
examples. This edition: Includes expanded coverage of Gibbs sampling, including
more numerical examples and treatments of OpenBUGS, R2WinBUGS and
R2OpenBUGS.
Wiley
Case Studies in Bayesian Statistical
Modelling and Analysis
9781119941828
16.11.2012
Oprawa: twarda
£ 65,00
Clair L. Alston
Case Studies in Bayesian Statistical Modelling and Analysis provides an accessible
foundation into Bayesian modelling and analysis using real-world models. Each
chapter comprises of a description of the problem, the corresponding model, the
computational method, results, and inferences as well as the issues that arise in the
implementation of these approaches. Coverage focuses on a real-world problems
drawn from the editors' own experiences while illustrating the way in which the
problem can be analyzed using Bayesian methods.
Wiley
Categorical Data Analysis with SAS and
SPSS Applications
9780415646413
03.05.2013
Oprawa: miękka
£ 28,00
Bayo Lawal
This book covers the fundamental aspects of categorical data analysis with an
emphasis on how to implement the models used in the book using SAS and SPSS.
This is accomplished through the frequent use of examples, with relevant codes and
instructions, that are closely related to the problems in the text. Concepts are
explained in detail so that students can reproduce similar results on their own.
Beginning with chapter two, exercises at the end of each chapter further strengthen
students' understanding of the concepts by requiring them to apply some of the
ideas expressed in the text in a more advanced capacity. Most of these exercises
require intensive use of PC-based statistical software. Numerous tables with results
of analyses, including interpretations of the results, further strengthen students'
understanding of the material.
Categorical Data Analysis With SAS(R) and SPSS Applications features:
detailed programs and outputs of all examples illustrated in the book using SAS
(R) 8.02 and SPSS on the book's CD;
Taylor & Francis
Causality: Statistical Perspectives and
Applications
9780470665565
13.07.2012
Oprawa: twarda
£ 55,00
Carlo Berzuini
This book looks at a broad collection of contributions from experts in their fields.
Providing a thorough treatment on statistical causality. Methods and their
applications are provided with theoretical background and emphasis is given to
practice rather than theory, with technical content kept to a minimum. Step-by-step
instructions for using the methods are presented with a broad range of examples,
including medicine, biology, economics, sociology and political science.
Wiley
7.
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Classic Problems of Probability
9781118063255
27.07.2012
Oprawa: miękka
£ 40,50
Prakash Gorroochurn
Classic Problems of Probability presents a lively account of the most intriguing
aspects of statistics. The book features a large collection of more than thirty classic
probability problems which have been carefully selected for their interesting history,
the way they have shaped the field, and their counterintuitive nature.
From Cardano's 1564 Games of Chance to Jacob Bernoulli's 1713 Golden
Theorem to Parrondo's 1996 Perplexing Paradox, the book clearly outlines the
puzzles and problems of probability, interweaving the discussion with rich historical
detail and the story of how the mathematicians involved arrived at their solutions.
Each problem is given an in-depth treatment, including detailed and rigorous
mathematical proofs as needed. Some of the fascinating topics discussed by the
author include:
Buffon's Needle problem and its ingenious treatment by Joseph Barbier,
culminating into a discussion of invariance
Various paradoxes raised by Joseph Bertrand
Wiley
CliffsNotes Statistics Quick Review
9780470902608
27.05.2011
Oprawa: miękka
£ 7,99
David H. Voelker
Inside the Book: Graphic displays Numerical measures Probability Sampling
Principles of testing Univariate inferential tests Bivariate relationships Review
questions Resource center Glossary Common mistakes Tables Why CliffsNotes? Go
with the name you know and trust Get the information you need-fast! CliffsNotes
Quick Review guides give you a clear, concise, easy-to-use review of the basics.
Introducing each topic, defining key terms, and carefully walking you through
sample problems, this guide helps you grasp and understand the important
concepts needed to succeed. Access 500 additional practice questions at
www.cliffsnotes.com/go/quiz/statistics Master the Basics--Fast Complete coverage
of core concepts Easy topic-by-topic organization Access hundreds of practice
problems at www.cliffsnotes.com/go/quiz/statistics
Wiley
Common Errors in Statistics (and How
to Avoid Them)
9781118294390
26.07.2012
Oprawa: miękka
£ 40,50
Phillip I. Good
Common Errors in Statistics (and How to Avoid Them), Fourth Edition provides a
mathematically rigorous, yet readily accessible foundation in statistics for
experienced readers as well as students learning to design and complete
experiments, surveys, and clinical trials.
Providing a consistent level of coherency throughout, the highly readable Fourth
Edition focuses on debunking popular myths, analyzing common mistakes, and
instructing readers on how to choose the appropriate statistical technique to
address their specific task. The authors begin with an introduction to the main
sources of error and provide techniques for avoiding them. Subsequent chapters
outline key methods and practices for accurate analysis, reporting, and model
building. The Fourth Edition features newly added topics, including:
Baseline data
Detecting fraud
Linear regression versus linear behavior
Wiley
Competing Risks and Multistate Models
with R
9781461420347
18.11.2011
Oprawa: miękka
€ 49,95
Jan Beyersmann
This book covers competing risks and multistate models, sometimes summarized
as event history analysis. These models generalize the analysis of time to a single
event (survival analysis) to analysing the timing of distinct terminal events (competing
risks) and possible intermediate events (multistate models). Both R and multistate
methods are promoted with a focus on nonparametric methods.
Springer
Confidence Intervals for Proportions
and Related Measures for Effect Size
9781439812785
20.09.2012
Oprawa: twarda
£ 57,99
Robert G. Newcombe
Confidence Intervals for Proportions and Related Measures of Effect Size illustrates
the use of effect size measures and corresponding confidence intervals as more
informative alternatives to the most basic and widely used significance tests. The
book provides you with a deep understanding of what happens when these
statistical methods are applied in situations far removed from the familiar Gaussian
case. Drawing on his extensive work as a statistician and professor at Cardiff
University School of Medicine, the author brings together methods for calculating
confidence intervals for proportions and several other important measures, including
differences, ratios, and nonparametric effect size measures generalizing Mann-
Whitney and Wilcoxon tests. He also explains three important approaches to
obtaining intervals for related measures. Many examples illustrate the application of
the methods in the health and social sciences. Requiring little computational skills,
the book offers user-friendly Excel spreadsheets for download at
www.crcpress.com, enabling you to easily apply the methods to your own empirical
data.
Taylor & Francis
Constrained Principal Component
Analysis and Related Techniques
9781466556669
16.11.2013
Oprawa: twarda
£ 57,99
Yoshio Takane
Despite the introduction of constrained principal component analysis (CPCA) over
20 years ago, there is no single resource that examines its ramifications, extensions,
implementations, and applications. This book explores how CPCA incorporates
external information into PCA of a main data matrix. It provides a systematic, in-
depth account of the mathematical underpinnings, special cases, related topics,
interesting applications, and implementation details. The author explains how CPCA
first decomposes the data matrix according to the external information (external
analysis) and then applies PCA to decomposed matrices (internal analysis).
Taylor & Francis
8.
Statystyka ogólna
8 www.abe.pl
Data Analysis Using Stata
9781597181105
21.09.2012
Oprawa: miękka
£ 49,99
Ulrich Kohler
Data Analysis Using Stata, Third Edition is a comprehensive introduction to both
statistical methods and Stata. Beginners will learn the logic of data analysis and
interpretation and easily become self-sufficient data analysts. Readers already
familiar with Stata will find it an enjoyable resource for picking up new tips and tricks.
The book is written as a self-study tutorial and organized around examples. It
interactively introduces statistical techniques such as data exploration, description,
and regression techniques for continuous and binary dependent variables. Step by
step, readers move through the entire process of data analysis and in doing so learn
the principles of Stata, data manipulation, graphical representation, and programs to
automate repetitive tasks. This third edition includes advanced topics, such as factor
-variables notation, average marginal effects, standard errors in complex survey, and
multiple imputation in a way, that beginners of both data analysis and Stata can
understand. Using data from a longitudinal study of private households, the authors
provide examples from the social sciences that are relatable to researchers from all
disciplines.
Taylor & Francis
Design and Analysis of Experiments
with Examples of SAS
9781420060607
03.05.2010
Oprawa: twarda
£ 66,99
John Lawson
A culmination of the author's many years of consulting and teaching, "Design and
Analysis of Experiments with SAS" provides practical guidance on the computer
analysis of experimental data. It connects the objectives of research to the type of
experimental design required, describes the actual process of creating the design
and collecting the data, shows how to perform the proper analysis of the data, and
illustrates the interpretation of results. Drawing on a variety of application areas, from
pharmaceuticals to machinery, the book presents numerous examples of
experiments and exercises that enable students to perform their own experiments.
Harnessing the capabilities of SAS 9.2, it includes examples of SAS data step
programming and IML, along with procedures from SAS Stat, SAS QC, and SAS
OR. The text also shows how to display experimental results graphically using SAS
codes graphics. The author emphasizes how the sample size, the assignment of
experimental units to combinations of treatment factor levels (error control), and the
selection of treatment factor combinations (treatment design) affect the resulting
variance and bias of estimates as well as the validity of conclusions.
Taylor & Francis
Design of Experiments: An Introduction
Based on Linear Models
9781584889236
27.07.2010
Oprawa: twarda
£ 62,99
Max Morris
Offering deep insight into the connections between design choice and the resulting
statistical analysis, Design of Experiments: An Introduction Based on Linear Models
explores how experiments are designed using the language of linear statistical
models. The book presents an organized framework for understanding the statistical
aspects of experimental design as a whole within the structure provided by general
linear models, rather than as a collection of seemingly unrelated solutions to unique
problems. The core material can be found in the first thirteen chapters. These
chapters cover a review of linear statistical models, completely randomized designs,
randomized complete blocks designs, Latin squares, analysis of data from
orthogonally blocked designs, balanced incomplete block designs, random block
effects, split-plot designs, and two-level factorial experiments. The remainder of the
text discusses factorial group screening experiments, regression model design, and
an introduction to optimal design. To emphasize the practical value of design, most
chapters contain a short example of a real-world experiment.
Taylor & Francis
Design of Observational Studies
9781441912121
06.11.2009
Oprawa: twarda
€ 76,95
Paul R. Rosenbaum
An observational study is an empiric investigation of effects caused by treatments
when randomized experimentation is unethical or infeasible. Observational studies
are common in most fields that study the effects of treatments on people, including
medicine, economics, epidemiology, education, psychology, political science and
sociology. The quality and strength of evidence provided by an observational study
is determined largely by its design. Design of Observational Studies is both an
introduction to statistical inference in observational studies and a detailed discussion
of the principles that guide the design of observational studies. Design of
Observational Studies is divided into four parts. Chapters 2, 3, and 5 of Part I cover
concisely, in about one hundred pages, many of the ideas discussed in
Rosenbaum's Observational Studies (also published by Springer) but in a less
technical fashion. Part II discusses the practical aspects of using propensity scores
and other tools to create a matched comparison that balances many covariates.
Part II includes a chapter on matching in R.
Springer
Dirichlet and Related Distributions
9780470688199
13.04.2011
Oprawa: twarda
£ 257,00
Kai Wang Ng
The Dirichlet distribution appears in many areas of application, which include
modelling of compositional data, Bayesian analysis, statistical genetics, and
nonparametric inference. This book provides a comprehensive review of the Dirichlet
distribution and two extended versions, the Grouped Dirichlet Distribution (GDD) and
the Nested Dirichlet Distribution (NDD), arising from likelihood and Bayesian analysis
of incomplete categorical data and survey data with non-response.
The theoretical properties and applications are also reviewed in detail for other
related distributions, such as the inverted Dirichlet distribution, Dirichlet-multinomial
distribution, the truncated Dirichlet distribution, the generalized Dirichlet distribution,
Hyper-Dirichlet distribution, scaled Dirichlet distribution, mixed Dirichlet distribution,
Liouville distribution, and the generalized Liouville distribution.
Wiley
Discovering Statistics Using IBM SPSS
Statistics
9781446249185
31.03.2013
Oprawa: miękka
£ 41,99
Andy Field
Unrivalled in the way it makes the teaching of statistics compelling and accessible to
even the most anxious of students, the only statistics textbook you and your
students will ever need just got better! Andy Field's bestselling Discovering Statistics
Using SPSS 4th Edition, already an immensely comprehensive textbook - taking
students from first principles to advanced statistical concepts, and all the while
grounding knowledge through the use of SPSS - now focuses on providing essential
updates, better accessibility to its key features, more instructor resources and
broader reach to new student groups - with powerful new digital developments on
the textbook's companion website. New to the 4th Edition - New WebAssign(R)
facility. If you adopt this for use on your course it will allow you to produce and
manage assignments online with your students and includes a grading facility to
monitor students' progress. Students can practise questions over and over and be
provided with instant feedback and links to the accompanying Ebook where correct
solutions can be found - The mobile study facility encourages students equipped
with smartphones and tablets to access revision material such as Cramming
SAGE
...
9.
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Discovering Statistics Using R
9781446200469
01.03.2012
Oprawa: miękka
£ 46,99
Field
Keeping the uniquely humorous and self-deprecating style that has made students
across the world fall in love with Andy Field's books, Discovering Statistics Using R
takes students on a journey of statistical discovery using R, a free, flexible and
dynamically changing software tool for data analysis that is becoming increasingly
popular across the social and behavioural sciences throughout the world.
The journey begins by explaining basic statistical and research concepts before a
guided tour of the R software environment. Next you discover the importance of
exploring and graphing data, before moving onto statistical tests that are the
foundations of the rest of the book (for example correlation and regression). You will
then stride confidently into intermediate level analyses such as ANOVA, before
ending your journey with advanced techniques such as MANOVA and multilevel
models. Although there is enough theory to help you gain the necessary conceptual
understanding of what you're doing, the emphasis is on applying what you learn to
playful and real-world examples that should make the experience more fun than you
might expect.
SAGE
Discovering Stats Using SAS
9781849200929
15.02.2010
Oprawa: miękka
£ 39,99
Field
Hot on the heels of the 3rd edition of Andy Field's award-winning Discovering
Statistics Using SPSS comes this brand new version for students using SAS®.
Andy has teamed up with a co-author, Jeremy Miles, to adapt the book with all the
most up-to-date commands and programming language from SAS® 9.2. If you're
using SAS®, this is the only book on statistics that you will need!
The book provides a comprehensive collection of statistical methods, tests and
procedures, covering everything you're likely to need to know for your course, all
presented in Andy's accessible and humourous writing style. Suitable for those new
to statistics as well as students on intermediate and more advanced courses, the
book walks students through from basic to advanced level concepts, all the while
reinforcing knowledge through the use of SAS®.
A 'cast of characters' supports the learning process throughout the book, from
providing tips on how to enter data in SAS® properly to testing knowledge covered
in chapters interactively, and 'real world' and invented examples illustrate the
concepts and make the techniques come alive.
SAGE
Elementary Statistics
9780321709981
01.01.2011
Oprawa: miękka
£ 56,99
Neil A. Weiss
Weiss's Elementary Statistics, Eighth Edition is the ideal textbook for introductory
statistics classes that emphasize statistical reasoning and critical thinking.
Comprehensive in its coverage, Weiss's meticulous style offers careful, detailed
explanations to ease the learning process. With more than 2,000 exercises, most
using real data, there is a wealth of opportunity for students to apply their
knowledge and develop statistical literacy. The text is suitable for a one-semester
course. Elementary Statistics, Eighth Edition, contains parallel presentation of critical
-value and p-value approaches to hypothesis testing. This unique design allows
both the flexibility to concentrate on one approach or the opportunity for greater
depth in comparing the two. This edition of Elementary Statistics continues the
book's tradition of being on the cutting edge of statistical pedagogy, technology,
and data analysis. It includes hundreds of new and updated exercises with real data
from journals, magazines, newspapers, and Web sites. Elementary Statistics, Eighth
Edition, takes a data-driven approach with more than 700 data sets documented by
several hundred data sources.
Pearson Education
Elementary Statistics
9780321894014
01.01.2013
Oprawa: twarda
£ 53,99
Mario F. Triola
From SAT scores to job search methods, statistics influences and shapes the world
around us. Marty Triola's text continues to be the bestseller because it helps
students understand the relationship between statistics and the world, bringing life
to the theory and methods. Elementary Statistics raises the bar with every edition by
incorporating an unprecedented amount of real and interesting data that will help
instructors connect with students today, and help them connect statistics to their
daily lives. The Twelfth Edition contains more than 1,800 exercises, 89% of which
use real data and 85% of which are new. Hundreds of examples are included, 91%
of which use real data and 84% of which are new. New coverage of Ethics in
Statistics highlights new guidelines that have been established in industry.
Pearson Education
Elementary Statistics Tables
9780415563475
04.08.2011
Oprawa: miękka
£ 17,99
H.R. Neave
This book, designed for students taking a basic introductory course in statistical
analysis, is far more than just a book of tables. Each table is accompanied by a
careful but concise explanation and useful worked examples. Requiring little
mathematical background, "Elementary Statistics Tables" is thus not just a reference
book but a positive and user-friendly teaching and learning aid.
Taylor & Francis
Elementary Statistics Using Excel
9780321890245
13.02.2013
Oprawa: twarda
£ 119,99
Mario F. Triola
From SAT scores to job search methods, statistics influences and shapes the world
around us. Marty Triola's text continues to be the bestseller because it helps
students understand the relationship between statistics and the world, bringing life
to the theory and methods. Elementary Statistics raises the bar with every edition by
incorporating an unprecedented amount of real and interesting data that will help
instructors connect with students today, and help them connect statistics to their
daily lives. The Twelfth Edition contains more than 1,800 exercises, 89% of which
use real data and 85% of which are new. Hundreds of examples are included, 91%
of which use real data and 84% of which are new. New coverage of Ethics in
Statistics highlights new guidelines that have been established in industry.
Pearson Education
10.
Statystyka ogólna
10 www.abe.pl
Elementary Statistics Using the TI-83/84
Plus Calculator
9780321641489
08.02.2010
Oprawa: twarda
£ 113,98
Mario F. Triola
95% of Introductory Statistics students will never take another Statistics course.
What do you want to learn? Discover the Power of Real Data Mario Triola remains
the market-leading statistics author by engaging readers of each edition with an
abundance of real data in the examples, applications, and exercises. Statistics is all
around us, and Triola helps readers understand how this course will impact their
lives beyond the classroom-as consumers, citizens, and professionals. Elementary
Statistics Using the TI-83/84 Plus Calculator, Third Edition provides extensive
instruction for using the TI-83 and TI-84 Plus (and Silver Edition) calculators for
statistics, with information on calculator functions, images of screen displays, and
projects designed exclusively for the graphing calculator. Drawn from Triola,s
Elementary Statistics, Eleventh Edition, this text provides the same student-friendly
approach with material presented in a real-world context. The Third Edition contains
more than 2,000 exercises, 87% are new, and 82% use real data. It also contains
hundreds of examples; 86% are new and 94% use real data.
Pearson Education
Elementary Statistics: Picturing the
World
9780321709974
24.12.2010
Oprawa: twarda
£ 67,99
Ron Larson
Elementary Statistics: Picturing the World, Fifth Edition, offers our most accessible
approach to statistics-with more than 750 graphical displays that illustrate data,
readers are able to visualize key statistical concepts immediately. Adhering to the
philosophy that students learn best by doing, this book relies heavily on examples-
25% of the examples and exercises are new for this edition. Larson and Farber
continue to demonstrate that statistics is all around us and that it's easy to
understand.
Pearson Education
Elements of Distribution Theory
9781107630734
24.10.2011
Oprawa: miękka
£ 29,99
Thomas A. Severini
This detailed introduction to distribution theory uses no measure theory, making it
suitable for students in statistics and econometrics as well as for researchers who
use statistical methods. Good backgrounds in calculus and linear algebra are
important and a course in elementary mathematical analysis is useful, but not
required. An appendix gives a detailed summary of the mathematical definitions and
results that are used in the book. Topics covered range from the basic distribution
and density functions, expectation, conditioning, characteristic functions, cumulants,
convergence in distribution and the central limit theorem to more advanced
concepts such as exchangeability, models with a group structure, asymptotic
approximations to integrals, orthogonal polynomials and saddlepoint
approximations. The emphasis is on topics useful in understanding statistical
methodology; thus, parametric statistical models and the distribution theory
associated with the normal distribution are covered comprehensively.
Cambridge University Press
Empirical Model Building: Data, Models,
and Reality
9780470467039
02.12.2011
Oprawa: twarda
£ 83,50
James R. Thompson
Praise for the First Edition "This...novel and highly stimulating book, which
emphasizes solving real problems...should be widely read. It will have a positive and
lasting effect on the teaching of modeling and statistics in general." - Short Book
Reviews This new edition features developments and real-world examples that
showcase essential empirical modeling techniques Successful empirical model
building is founded on the relationship between data and approximate
representations of the real systems that generated that data. As a result, it is
essential for researchers who construct these models to possess the special skills
and techniques for producing results that are insightful, reliable, and useful.
Empirical Model Building: Data, Models, and Reality, Second Edition presents a
hands-on approach to the basic principles of empirical model building through a
shrewd mixture of differential equations, computer-intensive methods, and data.
Wiley
Empirical Processes in M-estimation
9780521123259
19.01.2010
Oprawa: miękka
£ 28,99
Sara A. van de Geer
The theory of empirical processes provides valuable tools for the development of
asymptotic theory in (nonparametric) statistical models, and makes possible the
unified treatment of a number of them. This book reveals the relation between the
asymptotic behaviour of M-estimators and the complexity of parameter space.
Virtually all results are proved using only elementary ideas developed within the
book; there is minimal recourse to abstract theoretical results. To make the results
concrete, a detailed treatment is presented for two important examples of M-
estimation, namely maximum likelihood and least squares. The theory also covers
estimation methods using penalties and sieves. Many illustrative examples are given,
including the Grenander estimator, estimation of functions of bounded variation,
smoothing splines, partially linear models, mixture models and image analysis.
Graduate students and professionals in statistics as well as those with an interest in
applications, to such areas as econometrics, medical statistics, etc., will welcome
this treatment.
Cambridge University Press
Essentials of Statistical Inference
9780521548663
29.03.2010
Oprawa: miękka
£ 21,99
G.A. Young
Aimed at advanced undergraduate and graduate students in mathematics and
related disciplines, this 2005 book presents the concepts and results underlying the
Bayesian, frequentist and Fisherian approaches, with particular emphasis on the
contrasts between them. Computational ideas are explained, as well as basic
mathematical theory. Written in a lucid and informal style, this concise text provides
both basic material on the main approaches to inference, as well as more advanced
material on developments in statistical theory, including: material on Bayesian
computation, such as MCMC, higher-order likelihood theory, predictive inference,
bootstrap methods and conditional inference. It contains numerous extended
examples of the application of formal inference techniques to real data, as well as
historical commentary on the development of the subject. Throughout, the text
concentrates on concepts, rather than mathematical detail, while maintaining
appropriate levels of formality. Each chapter ends with a set of accessible problems.
Cambridge University Press
11.
Statystyka ogólna
www.abe.pl 11
Essentials of Statistics
9780321721693
30.04.2010
Oprawa: miękka
£ 56,99
Mario F. Triola
95% of Introductory Statistics students will never take another statistics course.
What do you want to learn? Discover the Power of Real Data Mario Triola remains
the market-leading statistics author by engaging readers of each edition with an
abundance of real data in the examples, applications, and exercises. Statistics is all
around us, and Triola helps readers understand how this course will impact their
lives beyond the classroom-as consumers, citizens, and professionals. Essentials of
Statistics, Fourth Edition is a more economical and streamlined introductory
statistics text. Drawn from Triola's Elementary Statistics, Eleventh Edition, this text
provides the same student-friendly approach with material presented in a real-world
context. The Fourth Edition contains more than 1,700 exercises (18% more than the
previous edition); 89% are new and 81% use real data. The book also contains
hundreds of examples; 86% are new and 92% use real data. By analyzing real data,
readers are able to connect abstract concepts to the world at large, teaching them
to think statistically and apply their conceptual understanding using the same
methods that professional statisticians employ.
Pearson Education
Essentials of Stochastic Processes
9781461436140
23.05.2012
Oprawa: twarda
€ 49,95
Richard Durrett
This book is for a first course in stochastic processes taken by undergraduates or
master,s students who have had a course in probability theory. It covers Markov
chains in discrete and continuous time, Poisson processes, renewal processes,
martingales, and mathematical finance. One can only learn a subject by seeing it in
action, so there are a large number of examples and more than 300 carefully chosen
exercises to deepen the reader,s understanding The book has undergone a
thorough revision since the first edition. There are many new examples and
problems with solutions that use the TI-83 to eliminate the tedious details of solving
linear equations by hand. Some material that was too advanced for the level has
been eliminated while the treatment of other topics useful for applications has been
expanded. In addition, the ordering of topics has been improved. For example, the
difficult subject of martingales is delayed until its usefulness can be seen in the
treatment of mathematical finance. Richard Durrett received his Ph.D. in Operations
Research from Stanford in 1976. He taught at the UCLA math department for nine
years and at Cornell for twenty-five before moving to Duke in 2010.
Springer
Everyday Probability and Statistics
9781848167629
07.08.2012
Oprawa: miękka
£ 31,00
Michael Mark Woolfson
Probability and statistics impinge on the life of the average person in a variety of
ways - as is suggested by the title of this book. Very often, information is provided
that is factually accurate but intended to present a biased view. This book presents
the important results of probability and statistics without making heavy mathematical
demands on the reader. It should enable an intelligent reader to properly assess
statistical information and to understand that the same information can be
presented in different ways. The author presents a new chapter exploring science
and society including the way that scientists communicate with the public on current
topics such as global warming. The book also investigates pensions and pension
policy, and how they are influenced by changing actuarial tables.
World Scientific Publishing
Expansions and Asymptotics for
Statistics
9781584885900
04.05.2010
Oprawa: twarda
£ 62,99
Christopher G. Small
Asymptotic methods provide important tools for approximating and analysing
functions that arise in probability and statistics. Moreover, the conclusions of
asymptotic analysis often supplement the conclusions obtained by numerical
methods. Providing a broad toolkit of analytical methods, Expansions and
Asymptotics for Statistics shows how asymptotics, when coupled with numerical
methods, becomes a powerful way to acquire a deeper understanding of the
techniques used in probability and statistics.
The book first discusses the role of expansions and asymptotics in statistics, the
basic properties of power series and asymptotic series, and the study of rational
approximations to functions. With a focus on asymptotic normality and asymptotic
efficiency of standard estimators, it covers various applications, such as the use of
the delta method for bias reduction, variance stabilisation, and the construction of
normalising transformations, as well as the standard theory derived from the work of
R.A. Fisher, H. Cramér, L. Le Cam, and others. The book then examines the close
connection between saddle-point approximation and the Laplace method.
Taylor & Francis
Fisher, Neyman, and the Creation of
Classical Statistics
9781441994998
03.08.2011
Oprawa: miękka
€ 26,95
Erich L. Lehmann
Classical statistical theory-hypothesis testing, estimation, and the design of
experiments and sample surveys-is mainly the creation of two men: Ronald A.
Fisher (1890-1962) and Jerzy Neyman (1894-1981). Their contributions sometimes
complemented each other, sometimes occurred in parallel, and, particularly at later
stages, often were in strong opposition. The two men would not be pleased to see
their names linked in this way, since throughout most of their working lives they
detested each other. Nevertheless, they worked on the same problems, and
through their combined efforts created a new discipline. This new book by E.L.
Lehmann, himself a student of Neyman's, explores the relationship between
Neyman and Fisher, as well as their interactions with other influential statisticians,
and the statistical history they helped create together. Lehmann uses direct
correspondence and original papers to recreate an historical account of the creation
of the Neyman-Pearson Theory as well as Fisher's dissent, and other important
statistical theories.
Springer
Frequency Curves and Correlation
9781107601291
30.06.2011
Oprawa: miękka
£ 16,99
William Palin Elderton
Originally published in 1906 by C. & E. Layton, Limited, this work, with its many later
improvements, became a standard textbook on curve-fitting and was several times
reissued. Reprinted here is the 1953 fourth edition of the book, published by
Cambridge University Press, and containing a preface by the author, Sir William
Elderton, in which he comments on the changes that he introduced.
Cambridge University Press
12.
Statystyka ogólna
12 www.abe.pl
From Finite Sample to Asymptotic
Methods in Statistics
9780521877220
03.01.2009
Oprawa: twarda
£ 54,00
Pranab Kumar Sen
Exact statistical inference may be employed in diverse fields of science and
technology. As problems become more complex and sample sizes become larger,
mathematical and computational difficulties can arise that require the use of
approximate statistical methods. Such methods are justified by asymptotic
arguments but are still based on the concepts and principles that underlie exact
statistical inference. With this in perspective, this book presents a broad view of
exact statistical inference and the development of asymptotic statistical inference,
providing a justification for the use of asymptotic methods for large samples.
Methodological results are developed on a concrete and yet rigorous mathematical
level and are applied to a variety of problems that include categorical data,
regression, and survival analyses. This book is designed as a textbook for advanced
undergraduate or beginning graduate students in statistics, biostatistics, or applied
statistics but may also be used as a reference for academic researchers.
Cambridge University Press
Functional Estimation for Density,
Regression Models and Processes
9789814343732
25.03.2011
Oprawa: twarda
£ 52,00
Odile Pons
This book presents a unified approach on nonparametric estimators for models of
independent observations, jump processes and continuous processes. New
estimators are defined and their limiting behavior is studied. From a practical point of
view, the book expounds on the construction of estimators for functionals of
processes and densities, and provides asymptotic expansions and optimality
properties from smooth estimators. It also presents new regular estimators for
functionals of processes, compares histogram and kernel estimators of several new
estimators for single-index models, and examines the weak convergence of the
estimators.
World Scientific Publishing
Generalized Linear Models: with
Applications in Engineering and the
9780470454633
16.04.2010
Oprawa: twarda
£ 83,50
Raymond H. Myers
Maintaining the same nontechnical approach as its acclaimed predecessor, this
second edition of Generalized Linear Models is now thoroughly extended to include
the latest developments in the field, the most relevant computational approaches,
and the most relevant examples from the fields of engineering and physical
sciences. This new edition is more tutorial in nature with added examples, exercises,
and step-by-step analyses that can be easily worked using the SAS, Minitab, JMP,
and R software packages. Its relevant for upper-undergraduate and graduate
students as well as engineers, scientists, and statisticians.
Wiley
Graphical Models with R
9781461422983
23.02.2012
Oprawa: miękka
€ 49,95
Soren Hojsgaard
Graphical models in their modern form have been around since the late 1970s and
appear today in many areas of the sciences. Along with the ongoing developments
of graphical models, a number of different graphical modeling software programs
have been written over the years. In recent years many of these software
developments have taken place within the R community, either in the form of new
packages or by providing an R interface to existing software. This book attempts to
give the reader a gentle introduction to graphical modeling using R and the main
features of some of these packages. In addition, the book provides examples of
how more advanced aspects of graphical modeling can be represented and
handled within R. Topics covered in the seven chapters include graphical models
for contingency tables, Gaussian and mixed graphical models, Bayesian networks
and modeling high dimensional data.
Springer
Handbook of Fitting Statistical
Distributions with R
9781584887119
01.10.2010
Oprawa: twarda
£ 101,00
Zaven A. Karian
Strengthened by examples taken from the scientific literature, this handbook
provides statisticians and researchers across the physical and social sciences with
cutting-edge methods for fitting continuous probability distributions. It presents
families with wide-ranging applicability, including Johnson's system, kappa
distribution, and generalized lambda distribution. By providing the necessary R
programs, the book enables practitioners to implement the techniques using R
computer code. To cover distribution method combinations not included in the
book's extensive tables, the authors delve into the application of computational
algorithms and attendant approximation errors.
Taylor & Francis
Handbook of Mixed Membership
Models and Their Applications
9781466504080
26.10.2013
Oprawa: twarda
£ 63,99
Edoardo M Airoldi (Harvard University, Massa-
Unlike classical mixture models that are limited by the assumption that each object
or individual belongs to only one mixture component, mixed membership models
handle various data structures and multivariate data of mixed types, including
longitudinal, sparse, and relational data structures. A compilation of peer-reviewed
articles from researchers in genetics and computer science, this volume examines
the characteristics of mixed membership distribution. It gives a fresh take on cluster
and classical modeling with a focus on posterior membership probabilities.
Taylor & Francis
13.
Statystyka ogólna
www.abe.pl 13
Handbook of Monte Carlo Methods
9780470177938
01.04.2011
Oprawa: twarda
£ 96,95
Dirk P. Kroese
More and more of today’s numerical problems found in engineering and finance are
solved through Monte Carlo methods. The heightened popularity of these methods
and their continuing development makes it important for researchers to have a
comprehensive understanding of the Monte Carlo approach. Handbook of Monte
Carlo Methods provides the theory, algorithms, and applications that helps provide a
thorough understanding of the emerging dynamics of this rapidly-growing field.
The authors begin with a discussion of fundamentals such as how to generate
random numbers on a computer. Subsequent chapters discuss key Monte Carlo
topics and methods, including:
Random variable and stochastic process generation
Markov chain Monte Carlo, featuring key algorithms such as the Metropolis-
Hastings method, the Gibbs sampler, and hit-and-run
Discrete-event simulation
Techniques for the statistical analysis of simulation data including the delta
method, steady-state estimation, and kernel density estimation
Wiley
Handbook of Parametric and
Nonparametric Statistical Procedures
9781439858011
02.05.2011
Oprawa: twarda
£ 115,00
David J. Sheskin
Following in the footsteps of its bestselling predecessors, the Handbook of
Parametric and Nonparametric Statistical Procedures, Fifth Edition provides
researchers, teachers, and students with an all-inclusive reference on univariate,
bivariate, and multivariate statistical procedures. New in the Fifth Edition:
Substantial updates and new material throughout New chapters on path analysis,
meta-analysis, and structural equation modeling Index numbers and time series
analysis applications in business and economics Statistical quality control
applications in industry Random- and fixed-effects models for the analysis of
variance Broad in scope, the Handbook is intended for individuals involved in a wide
spectrum of academic disciplines encompassing the fields of mathematics, the
social, biological, and environmental sciences, business, and education. A reference
for statistically sophisticated individuals, the Handbook is also accessible to those
lacking the theoretical or mathematical background required for understanding
subject matter typically documented in statistics reference books.
Taylor & Francis
Handbook of Spatial Point Pattern
Analysis in Ecology
9781420082548
25.10.2013
Oprawa: twarda
£ 49,99
Thorsten Wiegand
A guidebook to spatial point-pattern analysis for ecologists, this book provides a
comprehensive presentation of the theory behind point-pattern analysis targeted at
the non-expert. It contains case studies, worked examples, focus boxes, a
bibliography, and a glossary. The book uses Programita for the analysis of all
examples and includes detailed step-by-step instructions of how to perform the
analyses within the workbook. An executable copy of Programita and all example
data sets is available with the workbook. This book meets the growing need for a
resource focusing on the applications of point patterns analysis to ecological
problems.
Taylor & Francis
High-Dimensional Data Analysis
9789814324854
15.12.2010
Oprawa: twarda
£ 59,00
Tony Cai
Over the last few years, significant developments have been taking place in high-
dimensional data analysis, driven primarily by a wide range of applications in many
fields such as genomics and signal processing. In particular, substantial advances
have been made in the areas of feature selection, covariance estimation,
classification and regression. This book intends to examine important issues arising
from high-dimensional data analysis to explore key ideas for statistical inference and
prediction. It is structured around topics on multiple hypothesis testing, feature
selection, regression, classification, dimension reduction, as well as applications in
survival analysis and biomedical research. This book will appeal to graduate
students and new researchers interested in the plethora of opportunities available in
high-dimensional data analysis.
World Scientific Publishing
Incomplete Block Designs
9789814322683
31.08.2010
Oprawa: twarda
£ 52,00
Aloke Dey
This book presents a systematic, rigorous and comprehensive account of the theory
and applications of incomplete block designs. All major aspects of incomplete block
designs are considered by consolidating vast amounts of material from the literature
- the classical incomplete block designs, like the balanced incomplete block (BIB)
and partially balanced incomplete block (PBIB) designs. Other developments like
efficiency-balanced designs, nested designs, robust designs, C-designs and alpha
designs are also discussed, along with more recent developments in incomplete
block designs for special types of experiments, like biological assays, test-control
experiments and diallel crosses, which are generally not covered in existing books.
Results on the optimality aspects of various incomplete block designs are reviewed
in a separate chapter, that also includes recent results for test-control comparisons,
parallel-line assays and diallel cross experiments.
World Scientific Publishing
Incomplete Categorical Data Design:
Non-Randomized Response
9781439855331
16.08.2013
Oprawa: twarda
£ 57,99
Guo-Liang Tian
Unlike the established randomized response (RR) technique, non-randomized
response (NRR) techniques yield reproducible results in survey design and analysis.
This book presents new techniques designed to overcome the bias inherent in
posing sensitive questions in sociological or behavioral science surveys, without
requiring a means of randomization. The authors provide a systematic introduction
to NRR techniques that can overcome the limitations of RR techniques, combining
the strengths of existing approaches, such as RR models, incomplete data design,
expectation-maximization algorithm, data augmentation algorithm, and bootstrap
method.
Taylor & Francis
14.
Statystyka ogólna
14 www.abe.pl
Industrial Statistics: Practical Methods
and Guidance for Improved
9780470497166
14.04.2010
Oprawa: twarda
£ 53,50
Anand M. Joglekar
ndustrial Statistics guides you through ten practical statistical methods that have
broad applications in many different industries for enhancing research, product
design, process design, validation, manufacturing, and continuous improvement. As
you progress through the book, you'll discover some valuable methods that are
currently underutilized in industry as well as other methods that are often not used
correctly.
With twenty-five years of teaching and consulting experience, author Anand
Joglekar has helped a diverse group of companies reduce costs, accelerate product
development, and improve operations through the effective implementation of
statistical methods. Based on his experience working with both clients and
students, Dr. Joglekar focuses on real-world problem-solving. For each statistical
method, the book:
Presents the most important underlying concepts clearly and succinctly
Minimizes mathematical details that can be delegated to a computer
Illustrates applications with numerous practical examples
Wiley
Inequalities in Analysis and Probability
9789814412575
22.01.2013
Oprawa: twarda
£ 65,00
Odile Pons
The book is aimed at graduate students and researchers with basic knowledge of
Probability and Integration Theory. It introduces classical inequalities in vector and
functional spaces with applications to probability. It also develops new extensions of
the analytical inequalities, with sharper bounds and generalizations to the sum or the
supremum of random variables, to martingales and to transformed Brownian
motions. The proofs of the new results are presented in great detail.
World Scientific Publishing
Intro Stats
9780321891358
02.01.2013
Oprawa: twarda
£ 53,99
Richard D. De Veaux
Richard De Veaux, Paul Velleman, and David Bock wrote Intro Stats with the goal
that you have as much fun reading it as they did in writing it. Maintaining a
conversational, humorous, and informal writing style, this new edition engages
readers from the first page. The authors focus on statistical thinking throughout the
text and rely on technology for calculations. As a result, students can focus on
developing their conceptual understanding. Innovative Think/Show/Tell examples
provide a problem-solving framework and, more importantly, a way to think through
any statistics problem and present their results. New to the Fourth Edition is a
streamlined presentation that keeps students focused on what's most important,
while including out helpful features. An updated organization divides chapters into
sections, with specific learning objectives to keep students on track. A detailed table
of contents assists with navigation through this new layout. Single-concept
exercises complement the existing mid- to hard-level exercises for basic skill
development.
Pearson Education
Introduction to General and Generalized
Linear Models
9781420091557
05.11.2010
Oprawa: twarda
£ 41,99
Poul Thyregod
Since the mathematics behind generalized linear models is often difficult to follow
while the mathematics behind general linear models is well understood, this text
describes the methodology behind both models in a parallel setup. After introducing
a likelihood framework that is sufficient to cover both approaches, the authors
present general linear models, including analysis of covariance, before moving on to
more complicated generalized linear models using the same likelihood-based
approach. Numerous simulated and real-world examples, implemented using R and
SAS, illustrate the methods discussed. The text also provides exercises to further
develop understanding.
Taylor & Francis
Introduction to Linear Regression
Analysis
9780470542811
27.04.2012
Oprawa: twarda
£ 90,50
Douglas C. Montgomery
Praise for the Fourth Edition "As with previous editions, the authors have produced
a leading textbook on regression." -- Journal of the American Statistical Association
A comprehensive and up-to-date introduction to the fundamentals of regression
analysis Introduction to Linear Regression Analysis, Fifth Edition continues to
present both the conventional and less common uses of linear regression in today's
cutting-edge scientific research. The authors blend both theory and application to
equip readers with an understanding of the basic principles needed to apply
regression model-building techniques in various fields of study, including
engineering, management, and the health sciences. Following a general
introduction to regression modeling, including typical applications, a host of
technical tools are outlined such as basic inference procedures, introductory
aspects of model adequacy checking, and polynomial regression models and their
variations. The book then discusses how transformations and weighted least
squares can be used to resolve problems of model inadequacy and also how to
deal with influential observations.
Wiley
Introduction to Modeling and Analysis
of Stochastic Systems
9781441917713
10.11.2010
Oprawa: twarda
€ 79,95
V. G. Kulkarni
This book provides a self-contained review of all the relevant topics in probability
theory. A software package called MAXIM, which runs on MATLAB, is made
available for downloading. Vidyadhar G. Kulkarni is Professor of Operations
Research at the University of North Carolina at Chapel Hill.
Springer
15.
Statystyka ogólna
www.abe.pl 15
Introduction to the Theory of Statistical
Inference
9781439852927
25.07.2011
Oprawa: miękka
£ 31,99
Silvelyn Zwanzig
Based on the authors' lecture notes, Introduction to the Theory of Statistical
Inference presents concise yet complete coverage of statistical inference theory,
focusing on the fundamental classical principles. Suitable for a second-semester
undergraduate course on statistical inference, the book offers proofs to support the
mathematics. It illustrates core concepts using cartoons and provides solutions to all
examples and problems. Highlights Basic notations and ideas of statistical inference
are explained in a mathematically rigorous, but understandable, form Classroom-
tested and designed for students of mathematical statistics Examples, applications
of the general theory to special cases, exercises, and figures provide a deeper
insight into the material Solutions provided for problems formulated at the end of
each chapter Combines the theoretical basis of statistical inference with a useful
applied toolbox that includes linear models Theoretical, difficult, or frequently
misunderstood problems are marked The book is aimed at advanced
undergraduate students, graduate students in mathematics and statistics, and
theoretically-interested students from other disciplines.
Taylor & Francis
Introduction to Time Series Using Stata
9781597181327
08.02.2013
Oprawa: miękka
£ 49,99
Sean Becketti
Recent decades have witnessed explosive growth in new and powerful tools for
timeseries analysis. These innovations have overturned older approaches to
forecasting, macroeconomic policy analysis, the study of productivity and long-run
economic growth, and the trading of financial assets. Familiarity with these new
tools on time series is an essential skill for statisticians, econometricians, and
applied researchers. Introduction to Time Series Using Stata provides a step-by-
step guide to essential timeseries techniques-from the incredibly simple to the quite
complex-and, at the same time, demonstrates how these techniques can be applied
in the Stata statistical package. The emphasis is on an understanding of the intuition
underlying theoretical innovations and an ability to apply them. Real-world examples
illustrate the application of each concept as it is introduced, and care is taken to
highlight the pitfalls, as well as the power, of each new tool. Sean Becketti is a
financial industry veteran with three decades of experience in academics,
government, and private industry.
Taylor & Francis
Introductory Statistics
9780321740458
01.10.2010
Oprawa: twarda
£ 63,99
Neil A. Weiss
Weiss's Introductory Statistics, Ninth Edition is the ideal textbook for introductory
statistics classes that emphasize statistical reasoning and critical thinking. The text is
suitable for a one- or two-semester course. Comprehensive in its coverage, Weiss's
meticulous style offers careful, detailed explanations to ease the learning process.
With more than 1,000 data sets and more than 2,600 exercises, most using real
data, this text takes a data-driven approach that encourages students to apply their
knowledge and develop statistical literacy. Introductory Statistics, Ninth Edition,
contains parallel presentation of critical-value and p-value approaches to hypothesis
testing. This unique design allows both the flexibility to concentrate on one
approach or the opportunity for greater depth in comparing the two. This edition
continues the book's tradition of being on the cutting edge of statistical pedagogy,
technology, and data analysis. It includes hundreds of new and updated exercises
with real data from journals, magazines, newspapers, and websites. Datasets and
other resources (where applicable) for this book are available here.
Pearson Education
Introductory Statistics: A Conceptual
Approach Using R
9780415996006
17.12.2012
Oprawa: miękka
£ 60,00
William B. Ware
This comprehensive and uniquely organized text is aimed at undergraduate and
graduate level statistics courses in education, psychology, and other social
sciences. A conceptual approach, built around common issues and problems rather
than statistical techniques, allows students to understand the conceptual nature of
statistical procedures and to focus more on cases and examples of analysis.
Wherever possible, presentations contain explanations of the underlying reasons
behind a technique. Importantly, this is one of the first statistics texts in the social
sciences using R as the principal statistical package. Key features include the
following. Conceptual Focus - The focus throughout is more on conceptual
understanding and attainment of statistical literacy and thinking than on learning a
set of tools and procedures. Problems and Cases - Chapters and sections open
with examples of situations related to the forthcoming issues, and major sections
ends with a case study.
Taylor & Francis
Introductory Statistics: Exploring the
World Through Data
9780321322159
27.12.2011
Oprawa: twarda
£ 75,99
Robert Gould
We live in a data-driven world, and this is a book about understanding and working
with that data. In order to be informed citizens, authors Rob Gould and Colleen
Ryan believe that learning statistics extends beyond the classroom to an essential
life skill. They teach students of all math backgrounds how to think about data, how
to reason using data, and how to make decisions based on data. With a clear,
unintimidating writing style and carefully chosen pedagogy,Introductory Statistics:
Exploring the World through Data makes data analysis accessible to all students.
Guided Exercises support students by building their confidence as they learn to
solve problems. Snapshots summarize statistical procedures and concepts for
convenient studying. While this text assumes the use of statistical software, formulas
are presented as an aid to understanding the concepts rather than the focus of
study. Check Your Tech features demonstrate how students will get the same
numerical value by-hand as when using statistical software.
Pearson Education
Introductory Time Series with R
9780387886978
01.04.2009
Oprawa: miękka
€ 49,95
Paul S.P. Cowpertwait
Yearly global mean temperature and ocean levels, daily share prices, and the signals
transmitted back to Earth by the Voyager space craft are all examples of sequential
observations over time known as time series. This book gives you a step-by-step
introduction to analysing time series using the open source software R. Each time
series model is motivated with practical applications, and is defined in mathematical
notation. Once the model has been introduced it is used to generate synthetic data,
using R code, and these generated data are then used to estimate its parameters.
This sequence enhances understanding of both the time series model and the R
function used to fit the model to data. Finally, the model is used to analyse observed
data taken from a practical application. By using R, the whole procedure can be
reproduced by the reader. All the data sets used in the book are available on the
website http://www.massey.ac.nz/~pscowper/ts. The book is written for
undergraduate students of mathematics, economics, business and finance,
geography, engineering and related disciplines, and postgraduate students who
may need to analyse time series as part of their taught programme or their
Springer
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16.
Statystyka ogólna
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Kendalls Advanced Theory of Statistics
9780470669549
09.02.2010
Oprawa: twarda
£ 257,00
Alan Stuart
Wiley
Large Sample Inference for Long
Memory Processes
9781848162785
01.07.2010
Oprawa: twarda
£ 78,00
Liudas Giraitis
A discrete-time stationary stochastic process with finite variance is said to have long
memory if its autocorrelations tend to zero hyperbolically in the lag, i.e. like a power
of the lag, as the lag tends to infinity. The absolute sum of autocorrelations of such
processes diverges and their spectral density at the origin is unbounded. This is
unlike the so-called weakly dependent processes, where autocorrelations tend to
zero exponentially fast and the spectral density is bounded at the origin. In a long
memory process, the dependence between the current observation and the one at
a distant future is persistent; whereas in the weakly dependent processes, these
observations are approximately independent. This fact alone is enough to warn a
person about the validity of the classical inference procedures based on the square
root of the sample size standardization when data are generated by a long-term
memory process. The aim of this volume is to provide a text at the graduate level
from which one can learn, in a concise fashion, some basic theory and techniques
of proving limit theorems for numerous statistics based on long memory processes.
World Scientific Publishing
Large-Scale Inference
9781107619678
29.11.2012
Oprawa: miękka
£ 24,99
Bradley Efron
We live in a new age for statistical inference, where modern scientific technology
such as microarrays and fMRI machines routinely produce thousands and
sometimes millions of parallel data sets, each with its own estimation or testing
problem. Doing thousands of problems at once is more than repeated application of
classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of
the bootstrap, shows how information accrues across problems in a way that
combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in
this framework, producing opportunities for new methodologies of increased power.
New difficulties also arise, easily leading to flawed inferences. This book takes a
careful look at both the promise and pitfalls of large-scale statistical inference, with
particular attention to false discovery rates, the most successful of the new
statistical techniques. Emphasis is on the inferential ideas underlying technical
developments, illustrated using a large number of real examples.
Cambridge University Press
Latent Class and Latent Transition
Analysis
9780470228395
12.01.2010
Oprawa: twarda
£ 71,95
Linda M. Collins
One of the few books on latent class analysis (LCA) and latent transition analysis
(LTA) with a comprehensive treatment of longitudinal latent class models, Latent
Class and Latent Transition Analysis reflects improvements in statistical computing
as the most up-to-date reference for theoretical, technical, and practical issues in
cross-sectional and longitudinal data. Plentiful examples enable the reader to
acquire a thorough conceptual and technical understanding and to apply techniques
to address empirical research questions. Researchers seeking an advanced
introduction to LCA and LTA and graduate students will benefit from this text.
Wiley
Latent Variable Models and Factor
Analysis
9780470971925
15.07.2011
Oprawa: twarda
£ 55,00
David J. Bartholomew
Latent Variable Models and Factor Analysis provides a comprehensive and unified
approach to factor analysis and latent variable modeling from a statistical
perspective. This book presents a general framework to enable the derivation of the
commonly used models, along with updated numerical examples. Nature and
interpretation of a latent variable is also introduced along with related techniques for
investigating dependency. This book: Provides a unified approach showing how
such apparently diverse methods as Latent Class Analysis and Factor Analysis are
actually members of the same family. Presents new material on ordered manifest
variables, MCMC methods, non-linear models as well as a new chapter on related
techniques for investigating dependency. Includes new sections on structural
equation models (SEM) and Markov Chain Monte Carlo methods for parameter
estimation, along with new illustrative examples. Looks at recent developments on
goodness-of-fit test statistics and on non-linear models and models with mixed
latent variables, both categorical and continuous.
Wiley
Maximum Likelihood Estimation and
Inference
9780470094822
02.09.2011
Oprawa: twarda
£ 60,00
Russell B. Millar
This book takes a fresh look at the popular and well-established method of
maximum likelihood for statistical estimation and inference. It begins with an intuitive
introduction to the concepts and background of likelihood, and moves through to
the latest developments in maximum likelihood methodology, including general
latent variable models and new material for the practical implementation of
integrated likelihood using the free ADMB software. Fundamental issues of statistical
inference are also examined, with a presentation of some of the philosophical
debates underlying the choice of statistical paradigm. Key features: Provides an
accessible introduction to pragmatic maximum likelihood modelling. Covers more
advanced topics, including general forms of latent variable models (including non-
linear and non-normal mixed-effects and state-space models) and the use of
maximum likelihood variants, such as estimating equations, conditional likelihood,
restricted likelihood and integrated likelihood. Adopts a practical approach, with a
focus on providing the relevant tools required by researchers and practitioners who
collect and analyze real data.
Wiley
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Statystyka ogólna
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Methodology in Robust and
Nonparametric Statistics
9781439840689
30.07.2012
Oprawa: twarda
£ 63,99
Jana Jureckova
Robust and nonparametric statistical methods have their foundation in fields ranging
from agricultural science to astronomy, from biomedical sciences to the public
health disciplines, and, more recently, in genomics, bioinformatics, and financial
statistics. These disciplines are presently nourished by data mining and high-level
computer-based algorithms, but to work actively with robust and nonparametric
procedures, practitioners need to understand their background. Explaining the
underpinnings of robust methods and recent theoretical developments,
Methodology in Robust and Nonparametric Statistics provides a profound
mathematically rigorous explanation of the methodology of robust and
nonparametric statistical procedures. Thoroughly up-to-date, this book Presents
multivariate robust and nonparametric estimation with special emphasis on affine-
equivariant procedures, followed by hypotheses testing and confidence sets Keeps
mathematical abstractions at bay while remaining largely theoretical Provides a pool
of basic mathematical tools used throughout the book in derivations of main results
Taylor & Francis
Mixture
9781119993896
06.05.2011
Oprawa: twarda
£ 60,00
Christian Robert
This book uses the EM (expectation maximization) algorithm to simultaneously
estimate the missing data and unknown parameter(s) associated with a data set.
The parameters describe the component distributions of the mixture; the
distributions may be continuous or discrete.
The editors provide a complete account of the applications, mathematical structure
and statistical analysis of finite mixture distributions along with MCMC computational
methods, together with a range of detailed discussions covering the applications of
the methods and features chapters from the leading experts on the subject. The
applications are drawn from scientific discipline, including biostatistics, computer
science, ecology and finance. This area of statistics is important to a range of
disciplines, and its methodology attracts interest from researchers in the fields in
which it can be applied.
Wiley
Modelling Under Risk and Uncertainty
9780470695142
19.04.2012
Oprawa: twarda
£ 70,00
Etienne de Rocquigny
Modelling has permeated virtually all areas of industrial, environmental, economic,
bio-medical or civil engineering: yet the use of models for decision-making raises a
number of issues to which this book is dedicated: How uncertain is my model ? Is it
truly valuable to support decision-making ? What kind of decision can be truly
supported and how can I handle residual uncertainty ? How much refined should
the mathematical description be, given the true data limitations ? Could the
uncertainty be reduced through more data, increased modeling investment or
computational budget ? Should it be reduced now or later ? How robust is the
analysis or the computational methods involved ? Should / could those methods be
more robust ? Does it make sense to handle uncertainty, risk, lack of knowledge,
variability or errors altogether ? How reasonable is the choice of probabilistic
modeling for rare events ? How rare are the events to be considered? How far does
it make sense to handle extreme events and elaborate confidence figures ? Can I
take advantage of expert / phenomenological knowledge to tighten the probabilistic
figures ?
Wiley
Modern Elementary Statistics
9780131742581
21.11.2005
Oprawa: twarda
£ 55,26
Benjamin Perles
This book is intended for use in a first course in Statistics. There is a systematic
academic approach in "Modern Elementary Statistics". Its emphasis is on
introduction to meaningful, well-established statistical techniques. The future would
be medical doctor, business executive, scientist, teacher, or other professional
specialist must comprehend and be skillful in the application of baisc statistical tools
and methodology. The student's knowledge is greatly enhanced by repeated
exposure to statistical exercises.
Pearson Education
Modern Multivariate Statistical
Techniques
9780387781884
Aug 2008
Oprawa: twarda
€ 73,95
Alan Julian Izenman
This is the first book on multivariate analysis to look at large data sets which
describes the state of the art in analyzing such data. Material such as database
management systems is included that has never appeared in statistics books
before.
Springer
Modern Research Methods for the
Study of Behavior in Organizations
9780415885591
22.04.2013
Oprawa: twarda
£ 57,00
Jose M. Cortina
The goal for the chapters in this book SIOP Organizational Frontiers series volume
is to challenge researchers to break away from the rote application of traditional
methodologies and to capitalize upon the wealth of data collection and analytic
strategies available to them. In that spirit, many of the chapters in this book deal
with methodologies that encourage organizational scientists to re-conceptualize
phenomena of interest (e.g., experience sampling, catastrophe modeling), employ
novel data collection strategies (e.g., data mining, Petri nets), and/or apply
sophisticated analytic techniques (e.g., latent class analysis). The editors believe
that these chapters provide compelling solutions for the complex problems faced by
organizational researchers.
Taylor & Francis